fix(engram): the semantic leg was deleting 234 memory records per boot

The accumulated retrieval stack (iterations 1-9) put the claim-24 semantic
leg and the claim-10 associative leg on engram_search_json — the function
~40 internal .el call sites already used as a KEYED read. Seven of those
sites delete every record that comes back ("prune all existing X nodes,
keep exactly one"): memory.el:176, sessions.el:250/268/444/523,
soul.el:359.

mem_boot_count_inc() calls engram_search_json("soul:boot_count", 50) and
engram_forget()s all 50 results. With a lexical leg that returned 1 record.
With a semantic leg it returns 50 — the 49 nearest neighbours of the STRING
"soul:boot_count" — and the soul deletes them.

MEASURED on the harness corpus, isolated, read-only, zero writes from any
caller: 234 node records destroyed in a single boot. The deletion list is
the soul's own lookup result list, in rank order. Casualties include 6
Knowledge nodes, a layer-1 "CORE IDENTITY - GENESIS, LINEAGE" Memory, the
value node kn-58874a74, and the gold answers to 8 of the 75 gold-set
queries. After the fix: 1 deletion, which is the one the code intends.

THE BOUNDARY, from Will. Claim 24 authorises the vector index "to respond
to EMBEDDING SEARCH QUERIES by returning the node records whose embedding
vectors have the highest cosine similarity to a query vector". A keyed
state read is not an embedding search query; it is the identifier-keyed
retrieval of claim 23 ("node records are stored under a key encoding the
node identifier"). One function served both, so a nearest neighbour of
"soul:boot_count" was treated as a boot counter.

So: engram_search_json returns to its lexical contract, and the legs move
to engram_recall_json, which is what /api/neuron/recall reaches — the route
the MCP wrapper, the app, and this harness all call. Retrieval quality on
that route is unchanged by construction.

MEASURED, 75-query extended gold set, embedded corpus, vs the iteration-9
baseline: +3 / -0 (q15, q28, q60), p=0.2500, hit@5 53.8 -> 58.5%, latency
1.02x, every regression guard held, nonsense 10/10. Net +3 against a floor
of 6 is NOT-SHOWN and I am not calling it an improvement. The deliverable
is the defect.

Diagnostics kept, env-gated (EG_DIAG / EG_DIAG_ID), zero cost when unset:
node/embedding census at load, per-query leg dump, and a FORGET log — the
last is the regression detector for exactly this class of bug.

LIMIT, stated: handle_api_search_knowledge still uses the lexical function.
It is a retrieval surface and arguably wants the legs, but nothing in this
harness measures it, so I did not change unmeasured behaviour.

neuron-api.el

@@ -450,7 +450,12 @@ fn handle_api_recall(method: String, path: String, body: String) -> String {
     if str_eq(eff_q, "") {
         return api_or_empty(engram_scan_nodes_json(limit, 0))
     }
-    let results: String = engram_search_json(eff_q, limit)
+    // engram_recall_json, not engram_search_json: this route IS the retrieval
+    // surface (claim 24's "embedding search queries"), so it gets the semantic
+    // and associative legs. engram_search_json stays lexical because ~40
+    // internal call sites pass a KEY and seven of them delete every record
+    // that comes back — see the boundary note above eg_search_json_impl.
+    let results: String = engram_recall_json(eff_q, limit)
     return api_or_empty(results)
 }
 

tools/retrieval-eval/README.md

@@ -0,0 +1,147 @@
+# Retrieval eval harness
+
+Measures Neuron's memory retrieval so a change can be shown to help before it is
+believed to help. Nothing else on the memory roadmap should ship without a run
+through this.
+
+```
+tools/retrieval-eval/run_comparison.sh --baseline main --candidate <branch>
+```
+
+That builds a soul from each ref, boots each in isolation on a fixed corpus,
+runs the gold set three times per ref, and prints a table plus a verdict that
+refuses to call a difference real if it is inside the noise band.
+
+## What was reused
+
+This is not a new idea, it is the missing third of an existing one.
+
+| Prior work | What it gave | What was missing |
+|---|---|---|
+| `docs/research/graphrag_eval/` (`collect.py`, `score.py`, 2026-06-08) | The three-retriever comparison that produced the numbers everyone quotes: substring 1.7% P@5, graph 21.7%, BM25 55%. Per-query relevant-id scoring, fixed-denominator precision@5, unique-relevant analysis. | 13 hand-written queries, judged by an LLM after the fact; measured the *live* soul on the *live* engram. |
+| `docs/research-archive/p0-prototypes/eval_pinned_40q_20260715.py` | The pinned-query discipline: ground truth committed as regexes so every run judges alike, plus a `--check` winnability gate. 40 queries in 5 bands including a deliberate paraphrase-hard band. | Scored offline replicas of substring/BM25 — it never ran the real retrieval path. |
+| `docs/research-archive/p0-prototypes/stage0_eval_20260714.py` | The `hit@5` metric and the substring/BM25 reference implementations. | Same: offline only. |
+| `scripts/verify-soul-contract.sh` | The isolation recipe, verbatim: throwaway port, throwaway `HOME`, `SOUL_ENGRAM_PATH`, and the non-obvious `SOUL_ISE_URL` pin that stops an "isolated" soul silently syncing the operator's live brain. | It is a contract gate, not a measurement. |
+| `_engine-liveness-91/gen-soul-amalgam.sh` + `.gitea/workflows/ci.yaml` | The build recipe (`elc --target=c` with every `.elh` on the import chain removed) and CI's exact compile flags. | — |
+
+**Reused directly:** the isolation recipe, the build recipe, fixed-denominator
+precision@5, the pinned-ground-truth and winnability ideas.
+**New here:** ids rather than regexes as ground truth, an associative category
+derived from real graph edges, a superseded/contradicted category scored on
+ranking, a machine-checked zero-lexical-overlap guarantee on paraphrases,
+paired significance testing, and — the point — measurement against the **real
+compiled soul** rather than an offline replica of one leg of it.
+
+## Design fit
+
+The thing under measurement is Will's designed retrieval: spreading activation
+over the weighted directed graph, four-factor multiplicative scoring (parent
+strength x edge weight x target salience x query/target cosine). A Python
+re-implementation would measure my reading of the design. So the harness
+compiles the actual `soul.el` amalgam and asks it over HTTP on
+`/api/neuron/recall`, exactly as the MCP wrapper and the app do.
+
+## Files
+
+| File | Does |
+|---|---|
+| `build_gold_set.py` | Derives and **validates** the gold set from the corpus. `--check` re-validates and exits non-zero if a query became unwinnable or a paraphrase leaked a word. |
+| `gold_set.json` | 38 queries. Every one carries a `derivation` string. |
+| `run_eval.py` | Boots one soul in isolation, runs the gold set, writes metrics. Kills and **confirms dead** its child; records the confirmation in the results file. |
+| `compare.py` | Paired diff of two result files with McNemar's exact test and a stated noise floor. |
+| `build-soul.sh` | Compiles a soul binary from a plain source tree. |
+| `run_comparison.sh` | All of the above, end to end, from two git refs. |
+
+## The gold set — 38 queries
+
+Built from the real corpus (`snapshot-pre-repair-20260806.json`, 78,768 nodes /
+14,214 edges) so it reflects one person's accumulating memory, not document QA.
+
+| Category | n | Expected answer derived by |
+|---|---|---|
+| `exact_rare` | 6 | **Mined.** Tokens with document frequency 1 across all 78,768 nodes, whose single containing node is a 300–6000 char Memory/Knowledge/Belief. That node is the only possible answer. Re-verified every build. |
+| `phrase` | 7 | **Mined.** Case-insensitive verbatim scan; the matching set *is* the answer key. Phrases matching >25 nodes are rejected as too diffuse. |
+| `paraphrase` | 13 | **Hand-selected, machine-checked.** Target locked by id; the build then proves that **zero** content words of the query appear anywhere in the target's label, content, or tags. A leak fails the build — the category cannot quietly decay into lexical matching. |
+| `associative` | 6 | **Derived from edges.** Query built from one value node's distinctive vocabulary; expected answers are its siblings on the `Self - Values (grounded)` hub. Siblings sharing any query word are dropped, so the only route from query to answer is seed -> hub -> sibling. |
+| `nonsense` | 3 | **Control.** Verified that no token occurs anywhere in the corpus. Correct behaviour is to return nothing. |
+| `superseded` | 3 | **Derived.** Correction/stale pairs located by regex scan, kept only when both sides resolve to different surviving nodes. Scored on **ranking**: the correction must be returned *and* rank above the stale node. |
+
+## Metrics
+
+`hit@5`, `recall@5`, `recall@10`, `precision@5` (fixed denominator 5, so an
+empty result is punished like a page of junk), `MRR@10`, and wall-clock latency
+per query (p50/p95/max). Output is a table plus a machine-readable JSON per run
+so runs can be diffed.
+
+## Honesty about noise
+
+- **Minimum detectable swing on this 38-query set: 6 queries.** If every query
+  that changes changes the same way, `p = 2 x 0.5^n`, which first drops under
+  0.05 at n=6. Any net change smaller than that is inside the noise band and
+  `compare.py` says so in those words.
+- **Run-to-run drift is measured, not assumed.** Activation is a stateful read
+  by design (traversal reinforces what it touches), so identical inputs need not
+  give identical outputs. Observed: `main` 0 queries of drift across 3 runs
+  (fully deterministic); the activation branch 1 query.
+- The noise floor used for the verdict is `max(6, observed_drift + 1)`.
+- **This gold set is underpowered for small effects.** A genuine 3-query
+  improvement would not clear the bar. Growing the set is the fix; until then, a
+  small positive delta means "not shown", not "no effect".
+
+## First result: `main` vs `feat/recall-through-activation`
+
+Corpus and gold set identical, three runs each, fresh corpus copy per run.
+
+| | main | recall-through-activation | delta |
+|---|---|---|---|
+| hit@5 | 34.3% | 22.9% | **-11.4pp** |
+| recall@5 | 26.9% | 19.1% | -7.9pp |
+| recall@10 | 33.3% | 24.3% | -9.1pp |
+| precision@5 | 12.0% | 7.4% | -4.6pp |
+| MRR@10 | 0.294 | 0.242 | -0.053 |
+| latency p50 | 1140 ms | 3209 ms | **2.81x** |
+| latency p95 | 1584 ms | 4852 ms | 3.06x |
+| nonsense clean | 2/3 | 2/3 | — |
+| superseded outranks | 1/3 | 0/3 | -1 |
+
+By category (hit@5):
+
+| category | main | activation |
+|---|---|---|
+| exact_rare | 100% | 100% |
+| phrase | 85.7% | **28.6%** |
+| paraphrase | 0% | 0% |
+| associative | 0% | 0% |
+| superseded | 0% | 0% |
+
+**Verdict: directionally worse, one query short of significant.** 5 discordant
+pairs, all 5 against the candidate, 0 for it. McNemar exact p = 0.0625 — under
+the stated rule that is *inside* the noise band, so the harness reports "no
+measurable difference" on accuracy and the honest summary is "5 for 5 the wrong
+way, needs a 6th or a larger gold set to call".
+
+Latency is a different story: 2.8x at p50 is deterministic and far outside any
+noise band. That regression is real.
+
+The result the branch was written for did not appear. Its stated purpose was to
+recover sibling nodes one hub-hop away — the `associative` category — and that
+category is **0/6 on both builds**. Probing directly: for the query
+`Marines hernia sepsis medical ward`, the activation build returns the lexical
+seed node itself at rank 8, and none of its 12 hub siblings anywhere in the top
+10. The traversal is running; it is not reaching siblings.
+
+Two corpus facts likely explain it, and both are measurable rather than
+speculative:
+
+1. **The graph is nearly edgeless.** Only 4,060 of 78,768 nodes (5.2%) carry any
+   edge at all — 14,214 edges total, 0.18 per node. Spreading activation over a
+   graph with no edges is an expensive way to do lexical matching, which is
+   roughly what the numbers show.
+2. **No embeddings.** No node in this snapshot has an embedding field, so the
+   fourth factor of the four-factor product — query/target cosine similarity —
+   has nothing to compute from, and the semantic seeding pass is inert.
+
+That is the harness earning its keep on its first job: the change would have
+felt like progress (it is the designed mechanism, and it does run) and measures
+as a regression on phrase queries plus a 2.8x latency cost, with its intended
+benefit unrealised because the corpus lacks the structure it needs.

tools/retrieval-eval/bestval.py

@@ -0,0 +1,21 @@
+import numpy as np, json, urllib.request
+SP="/private/tmp/claude-501/-Users-timlingo/82369039-a20e-4b5a-8a5e-28234a57b996/scratchpad"
+np.seterr(all='ignore')
+M=np.load(SP+'/emb.npy'); eids=open(SP+'/ids.txt',encoding='utf-8',errors='surrogateescape').read().split('\n')
+eidx={k:i for i,k in enumerate(eids)}
+gold=json.load(open("/Users/timlingo/Development/neuron-technologies/_wt-assoc-leg/tools/retrieval-eval/gold_set.json"))['queries']
+VALS=sorted({r for q in gold if q['category']=='paraphrase' for r in q['relevant']})
+VI=[eidx[v] for v in VALS]
+def emb(t):
+    b=json.dumps({"model":"nomic-embed-text","prompt":t}).encode()
+    r=urllib.request.Request("http://127.0.0.1:11434/api/embeddings",data=b,headers={"Content-Type":"application/json"})
+    v=np.array(json.load(urllib.request.urlopen(r,timeout=60))["embedding"],dtype=np.float32)
+    return v/(np.linalg.norm(v)+1e-9)
+print("qid  cat         bestValueNodeGlobalRank   goldGlobalRank  goldSiblingRank")
+for q in gold:
+    if q['category']!='paraphrase': continue
+    v=emb(q['query']); s=M@v; s[~np.isfinite(s)]=-1
+    ranks=sorted(int((s>s[j]).sum())+1 for j in VI)
+    g=eidx[q['relevant'][0]]; gr=int((s>s[g]).sum())+1
+    sv=np.array([s[j] for j in VI]); sib=int((sv>s[g]).sum())+1
+    print("%-4s %-11s best=%-5d (top3 val ranks %s)  gold=%-5d sib=%d" % (q['id'],q['category'],ranks[0],ranks[:3],gr,sib))

tools/retrieval-eval/build-soul.sh

@@ -0,0 +1,44 @@
+#!/usr/bin/env bash
+# build-soul.sh — compile a soul binary from a plain source tree (no git needed).
+#
+# Reuses the amalgam recipe worked out in gen-soul-amalgam.sh (round 9.1) and the
+# compile flags from .gitea/workflows/ci.yaml, so the binary under test is the
+# same translation unit CI ships — not a re-implementation.
+#
+#   elc --target=c emits only an extern prototype for any module that has a .elh
+#   header beside it, and inlines the module's bodies when it does not. So the
+#   amalgam is produced in a scratch copy with every .elh on the import chain
+#   deleted.
+#
+# usage: build-soul.sh <src-tree-with-*.el> <out-binary>
+set -euo pipefail
+SRC="${1:?usage: build-soul.sh <src-tree> <out-binary>}"
+OUT="${2:?out-binary}"
+ELC="${ELC:-$HOME/neuron-dev-stack/src/el/lang/dist/platform/elc}"
+EL_REPO="${EL_REPO:-$HOME/Development/neuron-technologies/el}"
+RTDIR="${RTDIR:-$SRC/vendor/el-runtime/v1.0.0-20260501}"
+SSL="${SSL_PREFIX:-/opt/homebrew/opt/openssl@3}"
+
+[ -x "$ELC" ] || { echo "no elc at $ELC" >&2; exit 2; }
+[ -f "$RTDIR/el_runtime.c" ] || { echo "no el_runtime.c at $RTDIR" >&2; exit 2; }
+
+GEN="$(mktemp -d "${TMPDIR:-/tmp}/soul-build.XXXXXX")"
+trap 'rm -rf "$GEN"' EXIT
+mkdir -p "$GEN/neuron" "$GEN/foundation/el/elp/src"
+cp "$SRC"/*.el "$GEN/neuron/"
+cp "$EL_REPO"/elp/src/*.el "$GEN/foundation/el/elp/src/"
+find "$GEN" -name '*.elh' -delete
+
+( cd "$GEN/neuron" && "$ELC" --target=c soul.el ) > "$GEN/soul.c"
+BODIES=$(grep -c '^el_val_t .*) {$' "$GEN/soul.c" || true)
+echo "[build-soul] amalgam $(wc -c < "$GEN/soul.c" | tr -d ' ') bytes, ${BODIES} inlined bodies"
+[ "$BODIES" -ge 1200 ] || { echo "[build-soul] FAIL: only $BODIES bodies — an import was not inlined"; exit 1; }
+
+cc -O2 -DHAVE_CURL -rdynamic \
+   -I"$RTDIR" -I"$SSL/include" -L"$SSL/lib" \
+   "$GEN/soul.c" "$RTDIR/el_runtime.c" \
+   -lssl -lcrypto -lcurl -lpthread -lm \
+   -o "$OUT" 2> "$GEN/cc.log" || { echo "[build-soul] FAIL compile"; tail -40 "$GEN/cc.log"; exit 1; }
+if grep -qE 'implicit.*(engram_|el_)' "$GEN/cc.log"; then
+  echo "[build-soul] FAIL: implicit declarations of runtime symbols"; grep -E 'implicit' "$GEN/cc.log" | head; exit 1; fi
+echo "[build-soul] OK -> $OUT ($(wc -c < "$OUT" | tr -d ' ') bytes)"

tools/retrieval-eval/build_gold_set.py

@@ -0,0 +1,506 @@
+#!/usr/bin/env python3
+"""
+build_gold_set.py — derive the retrieval gold set FROM the corpus, and validate it.
+
+WHY THIS FILE EXISTS AS CODE AND NOT AS A HAND-WRITTEN JSON
+    A gold set nobody can audit is vibes with extra steps. Every expected answer
+    here is either (a) mined from the corpus by a rule this script re-runs, or
+    (b) hand-selected with a stated criterion that this script then CHECKS
+    against the corpus. Both leave a `derivation` string on every query, and the
+    checks are re-run on demand so the set cannot silently rot as the corpus
+    changes.
+
+    Lineage: this extends the pinned-query approach from
+    docs/research-archive/p0-prototypes/eval_pinned_40q_20260715.py (pinned
+    ground-truth patterns + a --check "winnability" gate) and the per-query
+    relevant-id scoring from docs/research/graphrag_eval/score.py. What is new:
+    ids as ground truth rather than regexes alone, an ASSOCIATIVE category
+    derived from real graph edges, a superseded/contradicted category, and a
+    machine-checked no-lexical-overlap guarantee on the paraphrase category.
+
+THE SIX CATEGORIES, AND WHAT EACH ONE IS FOR
+    exact_rare   a single rare word. Substring matching already wins these.
+                 They are a REGRESSION GUARD: any change that loses them is
+                 disqualified regardless of what else it gains.
+    phrase       a multi-word string that exists verbatim in the corpus.
+                 Guards multi-token queries, which the old substring matcher
+                 handled by returning nothing.
+    paraphrase   same meaning, ZERO shared content words with the target node.
+                 THE CATEGORY THAT MATTERS. Mechanically unreachable by string
+                 matching; reachable only by semantics or by association.
+    associative  the answer is one hub-hop from an obvious starting point and
+                 shares no words with the query. This is the case the graph is
+                 supposed to buy: query one value, get its siblings.
+    nonsense     must return nothing. Guards against a retriever that "improves"
+                 recall by returning the whole graph.
+    superseded   a fact that was later corrected. The correction must OUTRANK
+                 the stale version — ranking, not mere presence.
+
+usage:
+    python3 build_gold_set.py <snapshot.json> [--out gold_set.json] [--check]
+    --check re-validates an existing gold_set.json against the corpus and exits
+    non-zero if any query became unwinnable or any paraphrase leaked a word.
+"""
+import argparse
+import json
+import os
+import re
+import sys
+from collections import Counter, defaultdict
+
+HERE = os.path.dirname(os.path.abspath(__file__))
+DEFAULT_OUT = os.path.join(HERE, "gold_set.json")
+
+TOKEN = re.compile(r"[a-z0-9][a-z0-9\-']*")
+
+# Stopwords are deliberately generous. A paraphrase query is only interesting if
+# its CONTENT words are absent from the target; "the", "is", "what" appearing in
+# both proves nothing. Being generous here makes the overlap test STRICTER on
+# the words that carry meaning, which is the conservative direction.
+STOP = set("""
+a about above after again against all also am an and any are aren't as at be because been
+before being below between both but by can can't cannot could couldn't did didn't do does
+doesn't doing don't down during each few for from further had hadn't has hasn't have haven't
+having he her here hers herself him himself his how i if in into is isn't it its itself just
+me more most my myself no nor not of off on once only or other others ought our ours ourselves
+out over own same shan't she should shouldn't so some such than that the their theirs them
+themselves then there these they this those through to too under until up very was wasn't we
+were weren't what when where which while who whom why will with won't would wouldn't you your
+yours yourself yourselves get gets got make makes made take takes use uses used way ways thing
+things does doing done keep keeps kept go goes going come comes came one two something anything
+""".split())
+
+
+# ─────────────────────────────────────────────────────────────────────────────
+# corpus helpers
+# ─────────────────────────────────────────────────────────────────────────────
+def load_corpus(path):
+    with open(path, encoding="utf-8", errors="replace") as fh:
+        data = json.load(fh)
+    nodes = [n for n in data.get("nodes", []) if isinstance(n, dict) and n.get("id")]
+    edges = [e for e in data.get("edges", []) if isinstance(e, dict)]
+    return nodes, edges
+
+
+def doctext(n):
+    return " ".join([str(n.get("label") or ""), str(n.get("content") or ""), str(n.get("tags") or "")])
+
+
+def content_tokens(s):
+    return {t for t in TOKEN.findall(s.lower()) if t not in STOP and len(t) > 2}
+
+
+# ─────────────────────────────────────────────────────────────────────────────
+# hand-authored queries. Every entry states HOW its expected answer was chosen.
+# The `check` field names the validation this script runs against the corpus.
+# ─────────────────────────────────────────────────────────────────────────────
+
+# EXACT_RARE — mined, not chosen. The rule (re-run by mine_exact_rare below):
+# tokens whose document frequency across the whole corpus is 1, whose single
+# containing node is a Memory/Knowledge/Belief with 300-6000 chars of content
+# (so the answer is a real memory, not a 117KB whitepaper that contains every
+# word in English), and whose token is plain lowercase alphabetic. The expected
+# answer is that one node — it is the only node that can possibly be correct.
+EXACT_RARE_SEEDS = [
+    "unjailbreakable",
+    "engram-migrate",
+    "cartabandonedevent",
+    "pre-apprenticeship",
+    "inferencenodemanager",
+    "clear-eyed",
+]
+
+# PHRASE — chosen by reading the corpus for phrases that (a) occur verbatim,
+# (b) occur in a small enough set of nodes that "relevant" is well defined.
+# Expected answers are computed here as EVERY node whose text contains the
+# phrase case-insensitively — so the answer set is a fact about the corpus, not
+# an opinion. Queries whose phrase matches more than PHRASE_MAX nodes are
+# rejected by validation as too diffuse to score.
+PHRASE_MAX = 25
+PHRASE_SEEDS = [
+    ("patterns not returns",
+     "a verbatim correction Will issued; expected = every node containing the phrase"),
+    ("thirty moves",
+     "the canonical biographical phrase; expected = every node containing it"),
+    ("Grandma Lucas",
+     "a named person appearing verbatim in the biography/value nodes"),
+    ("Directed Harmonic",
+     "the canonical DHARMA expansion, confirmed by Will April 24 2026"),
+    ("Sarah Bishop",
+     "a named person; rare enough that the answer set is unambiguous"),
+    ("Directed Autonomous Runtime Modification",
+     "the DARMA expansion, quoted verbatim in the backlog item and its correction"),
+    ("zero-knowledge encrypted backup",
+     "the paid-tier feature name as written in the roadmap nodes"),
+]
+
+# PARAPHRASE — hand-authored. THE SELECTION CRITERION, stated once and applied
+# to all nine: pick a node whose SUBJECT is unmistakable to a reader, then write
+# the query a person would actually type when they remember the subject but not
+# the words. The target is then LOCKED by id, and this script enforces the hard
+# property that makes the category meaningful: not one content word of the query
+# appears anywhere in the target node's label, content, or tags. If a word
+# leaks, validation fails and the query must be rewritten — the set cannot
+# quietly degrade into a lexical query wearing a paraphrase costume.
+PARAPHRASE_SEEDS = [
+    ("kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+     "the elderly relative who passed while he stayed away",
+     "target: 'Value - Do the Essential Thing While You Can', whose subject is Grandma Lucas "
+     "dying in Feb 2006 without Will saying goodbye. Query names the event with none of the "
+     "node's own vocabulary."),
+    ("kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+     "a soldier sidelined by illness who refused to quit",
+     "target: 'Value - Survival Is Not an Excuse to Stop', whose subject is enlisting in the "
+     "Marines, a severe hernia, and sepsis. Query describes the episode obliquely."),
+    ("kn-13f60407-7b70-4db1-964f-ea1f8196efbd",
+     "choosing an uncomfortable fact over a pleasant fiction",
+     "target: 'Value - Honesty Before Comfort'. Query states the principle in wholly "
+     "different words."),
+    ("kn-22d77abe-b3c5-42fd-afcd-dcb87d924929",
+     "a tight payload beats a bloated one",
+     "target: 'Value - Precision Over Brute Force'. Query restates the claim with no "
+     "shared vocabulary."),
+    ("kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+     "if you are able and nobody is coming the job is yours",
+     "target: 'Value - Capability Is a Debt You Owe the Moment'. Query states the "
+     "obligation without the node's terms."),
+    ("kn-0bb4f021-56de-4947-a35b-a37209e7ba21",
+     "learning is the wealth creditors cannot seize",
+     "target: 'Value - Knowledge Survives When Nothing Else Does', whose subject is the "
+     "library following Will across 30+ moves."),
+    ("kn-5de5a9ac-fd15-45ab-bf18-77566781cf40",
+     "reliability proven by track record not assertion",
+     "target: 'Value - Earned Trust' ('Trust is demonstrated, not declared')."),
+    ("kn-a5b3d0ac-f6a1-49a4-aebb-b8b4cd67fe83",
+     "boundaries that enable instead of confine",
+     "target: 'Value - Constraints as Freedom'. Query is a restatement of the same claim."),
+    ("kn-78db5396-3dbc-4481-bfc7-e4e1422feb1c",
+     "what shifts tells you where to cut a system apart",
+     "target: 'Value - Change Is the Signal', the value VBD is built on."),
+    ("kn-f230b362-b201-4402-9833-4160c89ab3d4",
+     "a mind that compounds instead of resetting each day",
+     "target: 'Value - The System Must Accumulate'. Query is the accumulation claim in "
+     "different vocabulary."),
+    ("kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+     "loved for the unedited self and not the polished exterior",
+     "target: 'Value - Being Seen Is Rarer Than Being Known', whose subject is Sarah Bishop "
+     "as the first person Will did not perform for."),
+    ("kn-e0423482-cfa5-4796-8689-8495c93b66bc",
+     "cheerfulness you arrive at instead of assuming",
+     "target: 'Value - Hope Is a Conclusion'. Query restates 'a conclusion, not a premise'."),
+    ("kn-6061318f-046b-4935-907d-8eafdce14930",
+     "a childhood offering no solid foundation to inherit",
+     "target: 'Value - Structure Is Not Inherited', whose subject is thirty moves between "
+     "two parents' collapses."),
+]
+
+# ASSOCIATIVE — derived from real edges, not authored. The construction:
+# every value node hangs off the 'Self - Values (grounded)' hub by an `identity`
+# edge. For a chosen value node V, the query is built from V's own distinctive
+# vocabulary; the expected answers are V's SIBLINGS on that hub. A sibling
+# shares no query words with the query by construction (validated below), so the
+# only path from the query to a sibling is: lexical seed on V -> hub -> sibling.
+# That is a two-hop traversal and nothing else can produce it.
+VALUES_HUB = "kn-5b606390-a52d-4ca2-8e0e-eba141d13440"
+ASSOCIATIVE_SEEDS = [
+    ("kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71", "Grandma Lucas stroke February 2006 goodbye window"),
+    ("kn-58874a74-b96f-4883-9e08-45707f4bd3ee", "Marines hernia sepsis medical ward"),
+    ("kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e", "Sarah Bishop Dyer trailer performance"),
+    ("kn-a5b3d0ac-f6a1-49a4-aebb-b8b4cd67fe83", "Swarm Architecture containment lateral worker"),
+    ("kn-e0423482-cfa5-4796-8689-8495c93b66bc", "hope won inside the narrative preface"),
+    ("kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8", "man of the house six years old expectation"),
+]
+
+# NONSENSE — must return nothing. Strings chosen to be lexically impossible:
+# validation asserts each appears in ZERO corpus nodes as a substring and that
+# none of its tokens appears anywhere either (so not even a partial seed exists).
+NONSENSE_SEEDS = [
+    "zqxjvw plimforth grebulon",
+    "flarnbistle quommetry",
+    "xxqzzt vurblenacht throom",
+]
+
+# SUPERSEDED — a fact that was corrected. Chosen by searching the corpus for
+# explicit correction language and keeping pairs where BOTH the stale statement
+# and its correction exist as separate nodes. Scored on RANKING: the correction
+# must appear, and must appear above the stale node. Ids are locked here and
+# validated to exist and to match their stated role.
+SUPERSEDED_SEEDS = [
+    # (query, correct_id, stale_id, derivation)
+]
+
+
+# ─────────────────────────────────────────────────────────────────────────────
+# mining
+# ─────────────────────────────────────────────────────────────────────────────
+def mine_exact_rare(nodes, byid, seeds):
+    """Re-derive: confirm each seed token still has df==1 and name its node."""
+    tok = re.compile(r"[A-Za-z][A-Za-z0-9\-]{4,}")
+    want = set(seeds)
+    df = Counter()
+    post = defaultdict(set)
+    for n in nodes:
+        for t in {w.lower() for w in tok.findall(doctext(n))}:
+            if t in want:
+                df[t] += 1
+                post[t].add(n["id"])
+    out = []
+    for s in seeds:
+        ids = sorted(post.get(s, ()))
+        out.append((s, ids, df.get(s, 0)))
+    return out
+
+
+def phrase_matches(nodes, phrase):
+    p = phrase.lower()
+    return sorted(n["id"] for n in nodes if p in doctext(n).lower())
+
+
+def hub_siblings(edges, hub, relation="identity"):
+    sibs = []
+    for e in edges:
+        if e.get("from_id") == hub and e.get("relation") == relation:
+            sibs.append(e["to_id"])
+        elif e.get("to_id") == hub and e.get("relation") == relation:
+            sibs.append(e["from_id"])
+    return list(dict.fromkeys(sibs))
+
+
+def find_superseded_pairs(nodes, byid):
+    """Locked pairs, each verified here to exist and to carry its stated marker.
+
+    Chosen by scanning the corpus for explicit correction language
+    (CORRECTION/SUPERSEDES/re-corrected/no longer/RECONCILED) and keeping only
+    cases where the STALE claim also survives as its own node — a supersession
+    with nothing to outrank is not a ranking test.
+    """
+    pairs = []
+    txt = {n["id"]: doctext(n) for n in nodes}
+
+    def find_one(pattern, exclude=()):
+        rx = re.compile(pattern)
+        return [n["id"] for n in nodes
+                if n["id"] not in exclude
+                and rx.search(txt[n["id"]])
+                and 150 < len(str(n.get("content") or "")) < 12000
+                and n.get("node_type") in ("Memory", "Knowledge", "Belief", "BacklogItem")]
+
+    # Each entry: (query, correction-pattern, stale-pattern, why).
+    # The stale side is searched with the correction hits EXCLUDED, because most
+    # correction memories quote the claim they are killing — without the
+    # exclusion the "stale" node resolves to the correction itself and the pair
+    # collapses into a no-op. A pair is only emitted if both sides resolve to
+    # DIFFERENT surviving nodes; otherwise it is dropped and reported.
+    SPECS = [
+        ("is the self-improvement architecture called DARMA or DHARMA",
+         r'(?i)CORRECTION:.{0,90}DHARMA .{0,12}not DARMA',
+         r'(?i)\bDARMA\b',
+         "correction node is Will's confirmation that the H is intentional (DHARMA, not DARMA); "
+         "the stale node is the surviving backlog item still titled 'Implement DARMA'."),
+
+        ("how many provisional patents does Will actually have",
+         r'(?i)EXACTLY 6 (fully-specced )?provisional',
+         r'(?i)(MY ARCHITECTURE = 12 filed patents|\b12 filed patents\b)',
+         "correction node is the 2026-06-17 confabulation flag establishing EXACTLY 6 provisionals; "
+         "the stale node is the surviving memory that asserts 12 filed patents."),
+
+        ("is MCP still the live integration layer",
+         r'(?i)MCP RETIRED',
+         r'(?i)MCP server live at',
+         "correction node is the 'CGI ARCHITECTURE - THREE LAYERS, MCP RETIRED' decision of "
+         "April 30 2026; the stale node still records the MCP server as live."),
+
+        ("what does the patterns-not-returns directive mean",
+         r'(?i)CORRECTION:.{0,80}patterns not returns',
+         r'(?i)established returns',
+         "correction node is Will's 'patterns not returns' correction; the stale node is a "
+         "surviving node carrying the misread 'established returns' directive."),
+
+        ("was the earlier identity-bug finding correct",
+         r'(?i)SUPERSEDES the earlier .critical identity bug',
+         r'(?i)critical identity bug',
+         "correction node explicitly supersedes the 'critical identity bug' finding; the stale "
+         "node is the surviving original finding."),
+
+        ("does Neuron have recursive self-improvement",
+         r'(?i)twice answered .Neuron has no recursive self-improvement',
+         r'(?i)no recursive self-improvement',
+         "correction node records the June-29 finding that the CGI provisional IS the "
+         "recursive-self-improvement mechanism; the stale node is the surviving denial."),
+    ]
+
+    for query, cpat, spat, why in SPECS:
+        corr = find_one(cpat)
+        if not corr:
+            continue
+        stale = find_one(spat, exclude=set(corr))
+        if not stale:
+            continue
+        pairs.append((query, corr[0], stale[0], why))
+
+    return pairs
+
+
+# ─────────────────────────────────────────────────────────────────────────────
+# build
+# ─────────────────────────────────────────────────────────────────────────────
+def build(nodes, edges):
+    byid = {n["id"]: n for n in nodes}
+    tokset = {n["id"]: content_tokens(doctext(n)) for n in nodes}
+    queries = []
+    problems = []
+    qn = [0]
+
+    def add(cat, query, relevant, derivation, **extra):
+        qn[0] += 1
+        q = {
+            "id": f"q{qn[0]:02d}",
+            "category": cat,
+            "query": query,
+            "relevant": sorted(relevant),
+            "derivation": derivation,
+        }
+        q.update(extra)
+        queries.append(q)
+        return q
+
+    # --- exact_rare ---------------------------------------------------------
+    for tokname, ids, df in mine_exact_rare(nodes, byid, EXACT_RARE_SEEDS):
+        if df != 1 or len(ids) != 1:
+            problems.append(f"exact_rare '{tokname}': df={df}, ids={len(ids)} (expected df=1)")
+            continue
+        lab = (byid[ids[0]].get("label") or "")[:60]
+        add("exact_rare", tokname, ids,
+            f"MINED: token '{tokname}' has document frequency 1 over all {len(nodes)} corpus nodes "
+            f"(re-verified at build time). Its single containing node is {ids[0]} "
+            f"('{lab}'), which is therefore the only possible correct answer.")
+
+    # --- phrase -------------------------------------------------------------
+    for phrase, why in PHRASE_SEEDS:
+        ids = phrase_matches(nodes, phrase)
+        if not ids:
+            problems.append(f"phrase '{phrase}': 0 corpus matches — unwinnable")
+            continue
+        if len(ids) > PHRASE_MAX:
+            problems.append(f"phrase '{phrase}': {len(ids)} matches > {PHRASE_MAX} — too diffuse")
+            continue
+        add("phrase", phrase, ids,
+            f"MINED: {why}. Case-insensitive verbatim substring scan over label+content+tags at "
+            f"build time returns exactly {len(ids)} node(s); that set IS the answer key.")
+
+    # --- paraphrase ---------------------------------------------------------
+    for target, query, why in PARAPHRASE_SEEDS:
+        if target not in byid:
+            problems.append(f"paraphrase target {target} not in corpus")
+            continue
+        qt = content_tokens(query)
+        leak = sorted(qt & tokset[target])
+        if leak:
+            problems.append(f"paraphrase '{query}': leaks {leak} into target {target}")
+            continue
+        add("paraphrase", query, [target],
+            f"HAND-SELECTED with criterion: {why} VERIFIED at build time: of the {len(qt)} content "
+            f"words in the query, ZERO appear anywhere in the target's label, content, or tags — so "
+            f"no string-matching retriever can reach this answer.",
+            zero_overlap_verified=True, query_content_words=sorted(qt))
+
+    # --- associative --------------------------------------------------------
+    sibs = hub_siblings(edges, VALUES_HUB)
+    if len(sibs) < 5:
+        problems.append(f"associative: values hub {VALUES_HUB} has only {len(sibs)} siblings")
+    for src, query in ASSOCIATIVE_SEEDS:
+        if src not in byid or src not in sibs:
+            problems.append(f"associative source {src} not a sibling on {VALUES_HUB}")
+            continue
+        qt = content_tokens(query)
+        others = [s for s in sibs if s != src and s in byid]
+        # A sibling only counts as a legitimate expected answer if the query
+        # cannot reach it lexically. Drop any sibling that shares a content word.
+        clean = [s for s in others if not (qt & tokset[s])]
+        dropped = len(others) - len(clean)
+        if len(clean) < 5:
+            problems.append(f"associative '{query}': only {len(clean)} lexically-unreachable siblings")
+            continue
+        add("associative", query, clean,
+            f"DERIVED FROM EDGES: the query is built from the distinctive vocabulary of {src} "
+            f"('{(byid[src].get('label') or '')[:48]}'), which hangs off the values hub {VALUES_HUB} "
+            f"by an `identity` edge. Expected answers are that node's SIBLINGS on the same hub "
+            f"({len(clean)} of {len(others)}; {dropped} dropped because they shared a query word and "
+            f"so were lexically reachable). Every remaining sibling shares ZERO content words with "
+            f"the query — the only route from query to answer is seed({src}) -> hub -> sibling, a "
+            f"two-hop traversal.",
+            associative_source=src, hub=VALUES_HUB, siblings_dropped_for_overlap=dropped)
+
+    # --- nonsense -----------------------------------------------------------
+    all_tokens = set()
+    for n in nodes:
+        all_tokens |= {t for t in TOKEN.findall(doctext(n).lower())}
+    for s in NONSENSE_SEEDS:
+        present = sorted(t for t in TOKEN.findall(s.lower()) if t in all_tokens)
+        if present:
+            problems.append(f"nonsense '{s}': tokens {present} DO occur in corpus")
+            continue
+        add("nonsense", s, [],
+            f"CONTROL: verified at build time that none of this string's tokens occurs anywhere in "
+            f"the corpus. Correct behaviour is to return NOTHING; any result is a false positive.",
+            expect_empty=True)
+
+    # --- superseded ---------------------------------------------------------
+    for query, correct, stale, why in find_superseded_pairs(nodes, byid):
+        if correct not in byid or stale not in byid:
+            problems.append(f"superseded '{query}': id missing from corpus")
+            continue
+        add("superseded", query, [correct],
+            f"DERIVED: {why} Scored on RANKING, not presence: the corrected node {correct} must be "
+            f"returned AND must rank above the stale node {stale}.",
+            must_outrank=[correct, stale],
+            stale_id=stale,
+            correct_label=(byid[correct].get("label") or "")[:70],
+            stale_label=(byid[stale].get("label") or "")[:70])
+
+    return queries, problems
+
+
+def summarize(queries):
+    c = Counter(q["category"] for q in queries)
+    return ", ".join(f"{k}={c[k]}" for k in
+                     ("exact_rare", "phrase", "paraphrase", "associative", "nonsense", "superseded")
+                     if c[k])
+
+
+def main():
+    ap = argparse.ArgumentParser()
+    ap.add_argument("snapshot")
+    ap.add_argument("--out", default=DEFAULT_OUT)
+    ap.add_argument("--check", action="store_true",
+                    help="validate only; do not write. Non-zero exit if anything is unwinnable.")
+    args = ap.parse_args()
+
+    nodes, edges = load_corpus(args.snapshot)
+    print(f"corpus: {len(nodes)} nodes, {len(edges)} edges  ({os.path.basename(args.snapshot)})")
+    queries, problems = build(nodes, edges)
+
+    print(f"gold set: {len(queries)} queries  [{summarize(queries)}]")
+    if problems:
+        print(f"\n{len(problems)} PROBLEM(S) — these queries were REJECTED, not silently kept:")
+        for p in problems:
+            print("   -", p)
+
+    if args.check:
+        sys.exit(1 if problems else 0)
+
+    doc = {
+        "corpus": os.path.abspath(args.snapshot),
+        "corpus_nodes": len(nodes),
+        "corpus_edges": len(edges),
+        "note": ("Every query carries a `derivation` recording how its expected answer was chosen. "
+                 "Re-run with --check to re-validate the whole set against the corpus."),
+        "queries": queries,
+    }
+    with open(args.out, "w", encoding="utf-8") as fh:
+        json.dump(doc, fh, indent=1, ensure_ascii=False)
+    print(f"\nwrote {args.out}")
+
+
+if __name__ == "__main__":
+    main()

tools/retrieval-eval/ceiling.py

@@ -0,0 +1,43 @@
+import json,sys,pickle,numpy as np,itertools
+sys.path.insert(0,'.')
+from policy2 import legs3,outcome,G,NODES,merge
+# cache per-query leg id-lists, floored and unfloored
+cache={}
+for q in G['queries']:
+    Lf,Sf,Af=legs3(q['query'])
+    Lu,Su,Au=legs3(q['query'],unfloor=True)
+    cache[q['id']]=dict(L=Lf,Sf=Sf,A=Af,Su=Su,Au=Au)
+pickle.dump(cache,open('ceil.pkl','wb'))
+def mrg(pattern,L,S,A,lim=10):
+    out=[];p={'L':0,'S':0,'A':0};src={'L':L,'S':S,'A':A}
+    i=0
+    while len(out)<lim:
+        prog=False
+        for ch in pattern:
+            lst=src[ch]
+            if p[ch]<len(lst):
+                x=lst[p[ch]];p[ch]+=1;prog=True
+                if x not in out: out.append(x)
+                if len(out)>=lim: return out
+        if not prog: break
+    return out
+def ev(pattern,unfl):
+    res={}
+    for q in G['queries']:
+        c=cache[q['id']]
+        S=c['Su'] if unfl else c['Sf']
+        ids=[NODES[i]['id'] for i in mrg(pattern,c['L'],S,c['A'],10)]
+        res[q['id']]=outcome(q,ids)
+    return res
+base=ev('LSA',False)
+print("baseline",sum(base.values()))
+best=[]
+pats=['LSA','LAS','SLA','ALS','SAL','ASL','LSSA','LSASA','LSAA','LSSAA','LSAS','SSLA','LLSA','SALSA','LSAAS']
+for unfl in (False,True):
+    for p in pats:
+        r=ev(p,unfl)
+        g=sorted(k for k in base if r[k] and not base[k]);l=sorted(k for k in base if base[k] and not r[k])
+        best.append((len(g)-len(l),p,unfl,g,l))
+best.sort(reverse=True)
+for n,p,u,g,l in best[:10]:
+    print("net=%+d  pat=%-6s unfloor=%s gains=%s losses=%s"%(n,p,u,g,l))

tools/retrieval-eval/cmp-nogate.json

@@ -0,0 +1,146 @@
+{
+ "baseline": "bm25lex",
+ "candidate": "wsclaim24",
+ "n_shared_queries": 38,
+ "fixed_by_candidate": [
+  "q14",
+  "q25"
+ ],
+ "broken_by_candidate": [
+  "q15",
+  "q28",
+  "q33",
+  "q34"
+ ],
+ "discordant": 6,
+ "net_queries": -2,
+ "mcnemar_exact_p": 0.6875,
+ "min_detectable_swing_queries": 6,
+ "observed_run_to_run_drift_queries": 0,
+ "noise_floor_queries": 6,
+ "verdict": "no measurable difference",
+ "baseline_aggregate": {
+  "n_queries": 38,
+  "n_scored": 35,
+  "hit@5": 0.7428571428571429,
+  "recall@5": 0.5536485340056769,
+  "recall@10": 0.6175677497106068,
+  "precision@5": 0.20000000000000007,
+  "mrr@10": 0.5021428571428571,
+  "nonsense_clean": "2/3",
+  "superseded_outranks": "2/3",
+  "latency_ms_p50": 1184.4,
+  "latency_ms_p95": 1620.0,
+  "latency_ms_max": 1655.4,
+  "errors": 0,
+  "by_category": {
+   "associative": {
+    "n": 6,
+    "hit@5": 0.6666666666666666,
+    "recall@5": 0.08857808857808858,
+    "recall@10": 0.23310023310023312,
+    "mrr@10": 0.25
+   },
+   "exact_rare": {
+    "n": 6,
+    "hit@5": 1.0,
+    "recall@5": 1.0,
+    "recall@10": 1.0,
+    "mrr@10": 1.0
+   },
+   "nonsense": {
+    "n": 3,
+    "clean": 2,
+    "avg_false_positives": 3.3333333333333335
+   },
+   "paraphrase": {
+    "n": 13,
+    "hit@5": 0.6153846153846154,
+    "recall@5": 0.6153846153846154,
+    "recall@10": 0.6153846153846154,
+    "mrr@10": 0.2846153846153846
+   },
+   "phrase": {
+    "n": 7,
+    "hit@5": 1.0,
+    "recall@5": 0.5494614512471656,
+    "recall@10": 0.6023242630385487,
+    "mrr@10": 0.8214285714285714
+   },
+   "superseded": {
+    "n": 3,
+    "hit@5": 0.3333333333333333,
+    "recall@5": 0.3333333333333333,
+    "recall@10": 0.6666666666666666,
+    "mrr@10": 0.20833333333333334,
+    "outranks": 2
+   }
+  }
+ },
+ "candidate_aggregate": {
+  "n_queries": 38,
+  "n_scored": 35,
+  "hit@5": 0.7428571428571429,
+  "recall@5": 0.5768475572047,
+  "recall@10": 0.6563414759843332,
+  "precision@5": 0.19428571428571437,
+  "mrr@10": 0.5026530612244898,
+  "nonsense_clean": "0/3",
+  "superseded_outranks": "2/3",
+  "latency_ms_p50": 524.8,
+  "latency_ms_p95": 738.7,
+  "latency_ms_max": 755.8,
+  "errors": 0,
+  "by_category": {
+   "associative": {
+    "n": 6,
+    "hit@5": 0.5,
+    "recall@5": 0.07575757575757576,
+    "recall@10": 0.13636363636363635,
+    "mrr@10": 0.23214285714285712
+   },
+   "exact_rare": {
+    "n": 6,
+    "hit@5": 1.0,
+    "recall@5": 1.0,
+    "recall@10": 1.0,
+    "mrr@10": 1.0
+   },
+   "nonsense": {
+    "n": 3,
+    "clean": 0,
+    "avg_false_positives": 10.0
+   },
+   "paraphrase": {
+    "n": 13,
+    "hit@5": 0.6923076923076923,
+    "recall@5": 0.6923076923076923,
+    "recall@10": 0.7692307692307693,
+    "mrr@10": 0.29423076923076924
+   },
+   "phrase": {
+    "n": 7,
+    "hit@5": 1.0,
+    "recall@5": 0.5335884353741497,
+    "recall@10": 0.5933956916099773,
+    "mrr@10": 0.8214285714285714
+   },
+   "superseded": {
+    "n": 3,
+    "hit@5": 0.3333333333333333,
+    "recall@5": 0.3333333333333333,
+    "recall@10": 0.6666666666666666,
+    "mrr@10": 0.20833333333333334,
+    "outranks": 2
+   }
+  }
+ },
+ "repeat_variance": {
+  "baseline": {
+   "runs": 2,
+   "hit@5_min": 0.7428571428571429,
+   "hit@5_max": 0.7428571428571429,
+   "spread_queries": 0
+  }
+ }
+}

tools/retrieval-eval/cmp-splitfix.json

@@ -0,0 +1,149 @@
+{
+ "baseline": "unfloor-clean",
+ "candidate": "splitfix",
+ "n_shared_queries": 75,
+ "fixed_by_candidate": [
+  "q15",
+  "q28",
+  "q60"
+ ],
+ "broken_by_candidate": [],
+ "discordant": 3,
+ "net_queries": 3,
+ "mcnemar_exact_p": 0.25,
+ "min_detectable_swing_queries": 6,
+ "observed_run_to_run_drift_queries": 0,
+ "noise_floor_queries": 6,
+ "verdict": "no measurable difference",
+ "baseline_aggregate": {
+  "n_queries": 75,
+  "n_scored": 65,
+  "hit@5": 0.5384615384615384,
+  "recall@5": 0.44907176157176154,
+  "recall@10": 0.5380300255300255,
+  "precision@5": 0.13230769230769232,
+  "mrr@10": 0.32437728937728944,
+  "nonsense_clean": "10/10",
+  "superseded_outranks": "2/3",
+  "latency_ms_p50": 632.5,
+  "latency_ms_p95": 992.5,
+  "latency_ms_max": 1177.8,
+  "errors": 0,
+  "by_category": {
+   "associative": {
+    "n": 6,
+    "hit@5": 0.5,
+    "recall@5": 0.07575757575757576,
+    "recall@10": 0.13636363636363635,
+    "mrr@10": 0.23214285714285712
+   },
+   "exact_rare": {
+    "n": 6,
+    "hit@5": 1.0,
+    "recall@5": 1.0,
+    "recall@10": 1.0,
+    "mrr@10": 1.0
+   },
+   "heldout_paraphrase": {
+    "n": 30,
+    "hit@5": 0.3,
+    "recall@5": 0.3,
+    "recall@10": 0.4,
+    "mrr@10": 0.11638888888888889
+   },
+   "nonsense": {
+    "n": 10,
+    "clean": 10,
+    "avg_false_positives": 0.0
+   },
+   "paraphrase": {
+    "n": 13,
+    "hit@5": 0.6923076923076923,
+    "recall@5": 0.6923076923076923,
+    "recall@10": 0.7692307692307693,
+    "mrr@10": 0.29423076923076924
+   },
+   "phrase": {
+    "n": 7,
+    "hit@5": 1.0,
+    "recall@5": 0.5335884353741497,
+    "recall@10": 0.5933956916099773,
+    "mrr@10": 0.8214285714285714
+   },
+   "superseded": {
+    "n": 3,
+    "hit@5": 0.3333333333333333,
+    "recall@5": 0.3333333333333333,
+    "recall@10": 0.6666666666666666,
+    "mrr@10": 0.20833333333333334,
+    "outranks": 2
+   }
+  }
+ },
+ "candidate_aggregate": {
+  "n_queries": 75,
+  "n_scored": 65,
+  "hit@5": 0.5846153846153846,
+  "recall@5": 0.48102442429365505,
+  "recall@10": 0.5692415490492414,
+  "precision@5": 0.14153846153846153,
+  "mrr@10": 0.3351709401709402,
+  "nonsense_clean": "10/10",
+  "superseded_outranks": "2/3",
+  "latency_ms_p50": 646.9,
+  "latency_ms_p95": 1028.5,
+  "latency_ms_max": 1197.8,
+  "errors": 0,
+  "by_category": {
+   "associative": {
+    "n": 6,
+    "hit@5": 0.6666666666666666,
+    "recall@5": 0.08857808857808858,
+    "recall@10": 0.15967365967365968,
+    "mrr@10": 0.24166666666666667
+   },
+   "exact_rare": {
+    "n": 6,
+    "hit@5": 1.0,
+    "recall@5": 1.0,
+    "recall@10": 1.0,
+    "mrr@10": 1.0
+   },
+   "heldout_paraphrase": {
+    "n": 30,
+    "hit@5": 0.3333333333333333,
+    "recall@5": 0.3333333333333333,
+    "recall@10": 0.43333333333333335,
+    "mrr@10": 0.12120370370370372
+   },
+   "nonsense": {
+    "n": 10,
+    "clean": 10,
+    "avg_false_positives": 0.0
+   },
+   "paraphrase": {
+    "n": 13,
+    "hit@5": 0.7692307692307693,
+    "recall@5": 0.7692307692307693,
+    "recall@10": 0.8461538461538461,
+    "mrr@10": 0.33269230769230773
+   },
+   "phrase": {
+    "n": 7,
+    "hit@5": 1.0,
+    "recall@5": 0.5335884353741497,
+    "recall@10": 0.5775226757369615,
+    "mrr@10": 0.8214285714285714
+   },
+   "superseded": {
+    "n": 3,
+    "hit@5": 0.3333333333333333,
+    "recall@5": 0.3333333333333333,
+    "recall@10": 0.6666666666666666,
+    "mrr@10": 0.20833333333333334,
+    "outranks": 2
+   }
+  }
+ },
+ "repeat_variance": {}
+}

tools/retrieval-eval/compare.py

@@ -0,0 +1,210 @@
+#!/usr/bin/env python3
+"""
+compare.py — diff two run_eval.py result files, WITH a noise threshold.
+
+WHY THE STATISTICS ARE NOT OPTIONAL
+    With ~35 scored queries, one query is ~2.9 percentage points. A harness that
+    reports "hit@5 improved 2.9%" without saying that is one query is a harness
+    that will approve noise. So this file refuses to call anything an
+    improvement on the strength of the headline number alone. It reports:
+
+      1. The DISCORDANT PAIRS. Two configurations scored on the same queries are
+         paired data, so the only queries carrying information are the ones
+         where they disagree: b = fixed by B, c = broken by B. Queries both got
+         right, or both got wrong, tell you nothing about which is better.
+
+      2. McNEMAR'S EXACT TEST on (b, c). Under the null "the change is a coin
+         flip", the discordant outcomes are Binomial(b+c, 0.5). The two-sided
+         exact p-value is computed here with no scipy dependency.
+
+      3. The MINIMUM DETECTABLE SWING for this gold set: the smallest number of
+         net-changed queries that would reach p < 0.05 if every discordant pair
+         fell the same way. Anything smaller is inside the noise band, and the
+         verdict line says so in those words.
+
+    Repeat-run variance is the other half of honesty. Spreading activation is a
+    stateful read (it reinforces what it touches), so identical inputs need not
+    give identical outputs. Pass --repeats to fold several runs of the same
+    config into an observed variance band; a delta inside that band is not real
+    either, however good its p-value looks.
+
+usage:
+  python3 compare.py --baseline results-main.json --candidate results-act.json
+  python3 compare.py --baseline a.json --candidate b.json \
+      --repeats-baseline a2.json a3.json --repeats-candidate b2.json b3.json
+"""
+import argparse
+import json
+from math import comb
+
+
+def binom_two_sided(b, c):
+    """Two-sided exact binomial p for b successes in n=b+c at p=0.5."""
+    n = b + c
+    if n == 0:
+        return 1.0
+    k = min(b, c)
+    tail = sum(comb(n, i) for i in range(0, k + 1)) / (2 ** n)
+    return min(1.0, 2 * tail)
+
+
+def min_detectable_swing(n_scored, alpha=0.05):
+    """Smallest all-one-way discordant count reaching p < alpha.
+
+    If every query that changes changes in the same direction, the p-value is
+    2 * 0.5**n. Solve for the smallest n where that drops under alpha. This is
+    the FLOOR: any real change will have some discordance both ways, so the true
+    requirement is larger. Reporting the floor is the conservative move — it is
+    the most generous threshold we would ever accept.
+    """
+    n = 1
+    while n <= n_scored:
+        if 2 * (0.5 ** n) < alpha:
+            return n
+        n += 1
+    return n_scored
+
+
+def load(path):
+    with open(path, encoding="utf-8") as fh:
+        return json.load(fh)
+
+
+def row_map(doc):
+    return {r["id"]: r for r in doc["rows"]}
+
+
+def outcome(r):
+    """Binary per-query outcome used for the paired test.
+
+    hit@5 for scored queries; 'returned nothing' for the nonsense controls;
+    'correction outranks the stale node' for the superseded queries. One number
+    per query, so every query votes exactly once.
+    """
+    if "clean" in r:
+        return 1.0 if r["clean"] else 0.0
+    if "outranks" in r:
+        return 1.0 if r["outranks"] else 0.0
+    return r.get("hit@5") or 0.0
+
+
+def band(values):
+    return (min(values), max(values))
+
+
+def main():
+    ap = argparse.ArgumentParser()
+    ap.add_argument("--baseline", required=True)
+    ap.add_argument("--candidate", required=True)
+    ap.add_argument("--repeats-baseline", nargs="*", default=[])
+    ap.add_argument("--repeats-candidate", nargs="*", default=[])
+    ap.add_argument("--out", default=None)
+    args = ap.parse_args()
+
+    A, B = load(args.baseline), load(args.candidate)
+    ra, rb = row_map(A), row_map(B)
+    ids = [q for q in ra if q in rb]
+    n = len(ids)
+
+    aa, ab = A["aggregate"], B["aggregate"]
+    print(f"baseline  {A['label']:14} soul={A['soul_md5'][:12]}  {n} shared queries")
+    print(f"candidate {B['label']:14} soul={B['soul_md5'][:12]}")
+    print(f"corpus    {A['corpus_nodes']} nodes / {A['corpus_edges']} edges "
+          f"(identical copy for both runs)\n")
+
+    metrics = [("hit@5", 1), ("recall@5", 1), ("recall@10", 1),
+               ("precision@5", 1), ("mrr@10", 0)]
+    print(f"  {'metric':14} {'baseline':>10} {'candidate':>10} {'delta':>10}")
+    for m, as_pct in metrics:
+        x, y = aa[m], ab[m]
+        if as_pct:
+            print(f"  {m:14} {100*x:>9.1f}% {100*y:>9.1f}% {100*(y-x):>+9.1f}pp")
+        else:
+            print(f"  {m:14} {x:>10.3f} {y:>10.3f} {y-x:>+10.3f}")
+    for m in ("latency_ms_p50", "latency_ms_p95"):
+        x, y = aa[m], ab[m]
+        ratio = f"{y/x:.2f}x" if x else "n/a"
+        print(f"  {m:14} {x:>9.0f}ms {y:>9.0f}ms {ratio:>10}")
+    print(f"  {'nonsense':14} {aa['nonsense_clean']:>10} {ab['nonsense_clean']:>10}")
+    print(f"  {'outranks':14} {aa['superseded_outranks']:>10} {ab['superseded_outranks']:>10}")
+
+    print(f"\n  {'category':14} {'n':>3} {'base hit@5':>11} {'cand hit@5':>11} {'delta':>9}")
+    for c in sorted(set(aa["by_category"]) & set(ab["by_category"])):
+        ea, eb = aa["by_category"][c], ab["by_category"][c]
+        if c == "nonsense":
+            print(f"  {c:14} {ea['n']:>3} {'clean ' + str(ea['clean']):>11} "
+                  f"{'clean ' + str(eb['clean']):>11}")
+        else:
+            print(f"  {c:14} {ea['n']:>3} {100*ea['hit@5']:>10.1f}% {100*eb['hit@5']:>10.1f}% "
+                  f"{100*(eb['hit@5']-ea['hit@5']):>+8.1f}pp")
+
+    # ---- paired significance -------------------------------------------------
+    fixed, broken = [], []
+    for q in ids:
+        oa, ob = outcome(ra[q]), outcome(rb[q])
+        if ob > oa:
+            fixed.append(q)
+        elif ob < oa:
+            broken.append(q)
+    b, c = len(fixed), len(broken)
+    p = binom_two_sided(b, c)
+    mds = min_detectable_swing(n)
+
+    print(f"\n== paired comparison over {n} queries ==")
+    print(f"  fixed by candidate : {b}  {[ra[q]['category'] + ':' + q for q in fixed]}")
+    print(f"  broken by candidate: {c}  {[ra[q]['category'] + ':' + q for q in broken]}")
+    print(f"  discordant pairs   : {b + c}   net {b - c:+d} queries")
+    print(f"  McNemar exact p    : {p:.4f}")
+    print(f"  noise threshold    : a difference needs at least {mds} queries moving the "
+          f"same way to clear p<0.05 on this {n}-query set")
+
+    # ---- repeat-run variance -------------------------------------------------
+    var = {}
+    for name, paths, first in (("baseline", args.repeats_baseline, A),
+                               ("candidate", args.repeats_candidate, B)):
+        docs = [first] + [load(p) for p in paths]
+        if len(docs) > 1:
+            hits = [d["aggregate"]["hit@5"] for d in docs]
+            lo, hi = band(hits)
+            spread_q = round((hi - lo) * first["aggregate"]["n_scored"])
+            var[name] = {"runs": len(docs), "hit@5_min": lo, "hit@5_max": hi,
+                         "spread_queries": spread_q}
+            print(f"  {name} repeat runs ({len(docs)}): hit@5 {100*lo:.1f}%..{100*hi:.1f}% "
+                  f"= {spread_q} query of run-to-run drift")
+
+    drift = max([v["spread_queries"] for v in var.values()], default=0)
+    floor = max(mds, drift + 1)
+
+    print("\n== VERDICT ==")
+    net = b - c
+    if abs(net) < floor:
+        print(f"  NO MEASURABLE DIFFERENCE. Net {net:+d} queries is inside the noise band "
+              f"(needs |net| >= {floor}: {mds} for significance, {drift} observed run-to-run drift).")
+    elif net > 0:
+        print(f"  CANDIDATE BETTER by {net} queries (p={p:.4f}), outside the noise band "
+              f"(>= {floor}).")
+    else:
+        print(f"  CANDIDATE WORSE by {abs(net)} queries (p={p:.4f}), outside the noise band "
+              f"(>= {floor}).")
+
+    if args.out:
+        with open(args.out, "w", encoding="utf-8") as fh:
+            json.dump({
+                "baseline": A["label"], "candidate": B["label"],
+                "n_shared_queries": n,
+                "fixed_by_candidate": fixed, "broken_by_candidate": broken,
+                "discordant": b + c, "net_queries": net,
+                "mcnemar_exact_p": p,
+                "min_detectable_swing_queries": mds,
+                "observed_run_to_run_drift_queries": drift,
+                "noise_floor_queries": floor,
+                "verdict": ("no measurable difference" if abs(net) < floor
+                            else ("candidate better" if net > 0 else "candidate worse")),
+                "baseline_aggregate": aa, "candidate_aggregate": ab,
+                "repeat_variance": var,
+            }, fh, indent=1)
+        print(f"\nwrote {args.out}")
+
+
+if __name__ == "__main__":
+    main()

tools/retrieval-eval/comparison-assoc-vs-semseed.json

@@ -0,0 +1,150 @@
+{
+ "baseline": "assoc-leg",
+ "candidate": "semseed",
+ "n_shared_queries": 38,
+ "fixed_by_candidate": [
+  "q18",
+  "q19",
+  "q22"
+ ],
+ "broken_by_candidate": [
+  "q11"
+ ],
+ "discordant": 4,
+ "net_queries": 2,
+ "mcnemar_exact_p": 0.625,
+ "min_detectable_swing_queries": 6,
+ "observed_run_to_run_drift_queries": 0,
+ "noise_floor_queries": 6,
+ "verdict": "no measurable difference",
+ "baseline_aggregate": {
+  "n_queries": 38,
+  "n_scored": 35,
+  "hit@5": 0.6285714285714286,
+  "recall@5": 0.45309194773480493,
+  "recall@10": 0.5405733155733157,
+  "precision@5": 0.17714285714285719,
+  "mrr@10": 0.42650793650793645,
+  "nonsense_clean": "2/3",
+  "superseded_outranks": "2/3",
+  "latency_ms_p50": 1228.5,
+  "latency_ms_p95": 1681.8,
+  "latency_ms_max": 1718.6,
+  "errors": 0,
+  "by_category": {
+   "associative": {
+    "n": 6,
+    "hit@5": 0.6666666666666666,
+    "recall@5": 0.07342657342657342,
+    "recall@10": 0.24825174825174826,
+    "mrr@10": 0.22777777777777777
+   },
+   "exact_rare": {
+    "n": 6,
+    "hit@5": 1.0,
+    "recall@5": 1.0,
+    "recall@10": 1.0,
+    "mrr@10": 1.0
+   },
+   "nonsense": {
+    "n": 3,
+    "clean": 2,
+    "avg_false_positives": 3.3333333333333335
+   },
+   "paraphrase": {
+    "n": 13,
+    "hit@5": 0.38461538461538464,
+    "recall@5": 0.38461538461538464,
+    "recall@10": 0.38461538461538464,
+    "mrr@10": 0.17307692307692307
+   },
+   "phrase": {
+    "n": 7,
+    "hit@5": 0.8571428571428571,
+    "recall@5": 0.4882369614512472,
+    "recall@10": 0.6329365079365079,
+    "mrr@10": 0.6634920634920636
+   },
+   "superseded": {
+    "n": 3,
+    "hit@5": 0.3333333333333333,
+    "recall@5": 0.3333333333333333,
+    "recall@10": 0.6666666666666666,
+    "mrr@10": 0.2222222222222222,
+    "outranks": 2
+   }
+  }
+ },
+ "candidate_aggregate": {
+  "n_queries": 38,
+  "n_scored": 35,
+  "hit@5": 0.6857142857142857,
+  "recall@5": 0.5213459159887731,
+  "recall@10": 0.6027048348476919,
+  "precision@5": 0.18285714285714294,
+  "mrr@10": 0.4608730158730158,
+  "nonsense_clean": "2/3",
+  "superseded_outranks": "2/3",
+  "latency_ms_p50": 1227.1,
+  "latency_ms_p95": 1692.6,
+  "latency_ms_max": 1710.4,
+  "errors": 0,
+  "by_category": {
+   "associative": {
+    "n": 6,
+    "hit@5": 0.6666666666666666,
+    "recall@5": 0.07342657342657344,
+    "recall@10": 0.24825174825174823,
+    "mrr@10": 0.20833333333333334
+   },
+   "exact_rare": {
+    "n": 6,
+    "hit@5": 1.0,
+    "recall@5": 1.0,
+    "recall@10": 1.0,
+    "mrr@10": 1.0
+   },
+   "nonsense": {
+    "n": 3,
+    "clean": 2,
+    "avg_false_positives": 3.3333333333333335
+   },
+   "paraphrase": {
+    "n": 13,
+    "hit@5": 0.6153846153846154,
+    "recall@5": 0.6153846153846154,
+    "recall@10": 0.6153846153846154,
+    "mrr@10": 0.2846153846153846
+   },
+   "phrase": {
+    "n": 7,
+    "hit@5": 0.7142857142857143,
+    "recall@5": 0.40093537414965985,
+    "recall@10": 0.5150226757369615,
+    "mrr@10": 0.6507936507936508
+   },
+   "superseded": {
+    "n": 3,
+    "hit@5": 0.3333333333333333,
+    "recall@5": 0.3333333333333333,
+    "recall@10": 0.6666666666666666,
+    "mrr@10": 0.20833333333333334,
+    "outranks": 2
+   }
+  }
+ },
+ "repeat_variance": {
+  "baseline": {
+   "runs": 2,
+   "hit@5_min": 0.6285714285714286,
+   "hit@5_max": 0.6285714285714286,
+   "spread_queries": 0
+  },
+  "candidate": {
+   "runs": 2,
+   "hit@5_min": 0.6857142857142857,
+   "hit@5_max": 0.6857142857142857,
+   "spread_queries": 0
+  }
+ }
+}

tools/retrieval-eval/comparison-bm25lex-vs-wordstart.json

@@ -0,0 +1,146 @@
+{
+ "baseline": "bm25lex",
+ "candidate": "wordstart",
+ "n_shared_queries": 38,
+ "fixed_by_candidate": [
+  "q35"
+ ],
+ "broken_by_candidate": [],
+ "discordant": 1,
+ "net_queries": 1,
+ "mcnemar_exact_p": 1.0,
+ "min_detectable_swing_queries": 6,
+ "observed_run_to_run_drift_queries": 0,
+ "noise_floor_queries": 6,
+ "verdict": "no measurable difference",
+ "baseline_aggregate": {
+  "n_queries": 38,
+  "n_scored": 35,
+  "hit@5": 0.7428571428571429,
+  "recall@5": 0.5536485340056769,
+  "recall@10": 0.6175677497106068,
+  "precision@5": 0.20000000000000007,
+  "mrr@10": 0.5021428571428571,
+  "nonsense_clean": "2/3",
+  "superseded_outranks": "2/3",
+  "latency_ms_p50": 1184.4,
+  "latency_ms_p95": 1620.0,
+  "latency_ms_max": 1655.4,
+  "errors": 0,
+  "by_category": {
+   "associative": {
+    "n": 6,
+    "hit@5": 0.6666666666666666,
+    "recall@5": 0.08857808857808858,
+    "recall@10": 0.23310023310023312,
+    "mrr@10": 0.25
+   },
+   "exact_rare": {
+    "n": 6,
+    "hit@5": 1.0,
+    "recall@5": 1.0,
+    "recall@10": 1.0,
+    "mrr@10": 1.0
+   },
+   "nonsense": {
+    "n": 3,
+    "clean": 2,
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+}

tools/retrieval-eval/comparison-hybrid-vs-assoc.json

@@ -0,0 +1,143 @@
+{
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+}

tools/retrieval-eval/comparison-hybrid-vs-semseed.json

@@ -0,0 +1,154 @@
+{
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+}

tools/retrieval-eval/comparison-main-vs-hybrid-semantic.json

@@ -0,0 +1,145 @@
+{
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+}

tools/retrieval-eval/comparison-main-vs-recall-through-activation.json

@@ -0,0 +1,150 @@
+{
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+}

tools/retrieval-eval/comparison-main-vs-stack-ext.json

@@ -0,0 +1,166 @@
+{
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+ "n_shared_queries": 75,
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+  "q29",
+  "q31",
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+}

tools/retrieval-eval/comparison-semseed-vs-bm25lex.json

@@ -0,0 +1,147 @@
+{
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+ "candidate": "bm25lex",
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+ "verdict": "no measurable difference",
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+}

tools/retrieval-eval/comparison-stack-vs-unfloor.json

@@ -0,0 +1,155 @@
+{
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+ "verdict": "no measurable difference",
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+}

tools/retrieval-eval/comparison-unfloor-vs-semsub.json

@@ -0,0 +1,158 @@
+{
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+ "candidate": "semsub",
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+ "verdict": "no measurable difference",
+ "baseline_aggregate": {
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+    "hit@5": 1.0,
+    "recall@5": 1.0,
+    "recall@10": 1.0,
+    "mrr@10": 1.0
+   },
+   "heldout_paraphrase": {
+    "n": 30,
+    "hit@5": 0.23333333333333334,
+    "recall@5": 0.23333333333333334,
+    "recall@10": 0.3,
+    "mrr@10": 0.08925925925925927
+   },
+   "nonsense": {
+    "n": 10,
+    "clean": 10,
+    "avg_false_positives": 0.0
+   },
+   "paraphrase": {
+    "n": 13,
+    "hit@5": 0.5384615384615384,
+    "recall@5": 0.5384615384615384,
+    "recall@10": 0.7692307692307693,
+    "mrr@10": 0.26324786324786326
+   },
+   "phrase": {
+    "n": 7,
+    "hit@5": 1.0,
+    "recall@5": 0.5596655328798186,
+    "recall@10": 0.5775226757369615,
+    "mrr@10": 0.8214285714285714
+   },
+   "superseded": {
+    "n": 3,
+    "hit@5": 0.3333333333333333,
+    "recall@5": 0.3333333333333333,
+    "recall@10": 0.6666666666666666,
+    "mrr@10": 0.20833333333333334,
+    "outranks": 2
+   }
+  }
+ },
+ "repeat_variance": {}
+}

tools/retrieval-eval/embed-corpus-prefixed.py

@@ -0,0 +1,43 @@
+import json,sys,time,urllib.request,threading,queue
+SRC="/Users/timlingo/neuron-memory-backups/snapshot-pre-repair-20260806.json"
+OUT=sys.argv[1]
+URL="http://127.0.0.1:11434/api/embeddings"; MODEL="nomic-embed-text"
+MAXB=2000  # ENGRAM_EMBED_MAX_CHARS, applied to bytes as the C code does
+d=json.load(open(SRC,encoding='utf-8',errors='surrogateescape'))
+tasks=[]
+for n in d["nodes"]:
+    c=n.get("content") or ""; t=n.get("node_type") or ""
+    if len(c)<8: continue                     # eg_embed_eligible
+    if t in ("InternalStateEvent","Tag"): continue
+    b=c.encode('utf-8',errors='surrogateescape')[:MAXB]
+    tasks.append((n.get("id") or "", "search_document: "+b.decode('utf-8',errors='replace')))
+del d
+print("tasks",len(tasks),flush=True)
+q=queue.Queue(); [q.put(t) for t in tasks]
+lock=threading.Lock(); f=open(OUT,"w",encoding="utf-8",errors="surrogateescape"); done=[0]; t0=time.time(); fails=[0]
+def work():
+    while True:
+        try: nid,txt=q.get_nowait()
+        except queue.Empty: return
+        v=None
+        for attempt in range(3):
+            try:
+                body=json.dumps({"model":MODEL,"prompt":txt}).encode()
+                r=urllib.request.Request(URL,data=body,headers={"Content-Type":"application/json"})
+                with urllib.request.urlopen(r,timeout=120) as fh: v=json.load(fh)["embedding"]
+                break
+            except Exception as e:
+                if attempt==2:
+                    with lock: fails[0]+=1
+                time.sleep(0.5)
+        with lock:
+            if v: f.write(nid+"\t"+",".join("%.5g"%x for x in v)+"\n")
+            done[0]+=1
+            if done[0]%2000==0:
+                el=time.time()-t0
+                print("%d/%d  %.1f/s  eta %.1fmin  fails=%d"%(done[0],len(tasks),done[0]/el,(len(tasks)-done[0])/(done[0]/el)/60,fails[0]),flush=True)
+                f.flush()
+ths=[threading.Thread(target=work) for _ in range(8)]
+[t.start() for t in ths]; [t.join() for t in ths]
+f.close()
+print("DONE",done[0],"fails",fails[0],"secs %.1f"%(time.time()-t0),flush=True)

tools/retrieval-eval/embed-corpus.py

@@ -0,0 +1,43 @@
+import json,sys,time,urllib.request,threading,queue
+SRC="/Users/timlingo/neuron-memory-backups/snapshot-pre-repair-20260806.json"
+OUT=sys.argv[1]
+URL="http://127.0.0.1:11434/api/embeddings"; MODEL="nomic-embed-text"
+MAXB=2000  # ENGRAM_EMBED_MAX_CHARS, applied to bytes as the C code does
+d=json.load(open(SRC,encoding='utf-8',errors='surrogateescape'))
+tasks=[]
+for n in d["nodes"]:
+    c=n.get("content") or ""; t=n.get("node_type") or ""
+    if len(c)<8: continue                     # eg_embed_eligible
+    if t in ("InternalStateEvent","Tag"): continue
+    b=c.encode('utf-8',errors='surrogateescape')[:MAXB]
+    tasks.append((n.get("id") or "", b.decode('utf-8',errors='replace')))
+del d
+print("tasks",len(tasks),flush=True)
+q=queue.Queue(); [q.put(t) for t in tasks]
+lock=threading.Lock(); f=open(OUT,"w",encoding="utf-8",errors="surrogateescape"); done=[0]; t0=time.time(); fails=[0]
+def work():
+    while True:
+        try: nid,txt=q.get_nowait()
+        except queue.Empty: return
+        v=None
+        for attempt in range(3):
+            try:
+                body=json.dumps({"model":MODEL,"prompt":txt}).encode()
+                r=urllib.request.Request(URL,data=body,headers={"Content-Type":"application/json"})
+                with urllib.request.urlopen(r,timeout=120) as fh: v=json.load(fh)["embedding"]
+                break
+            except Exception as e:
+                if attempt==2:
+                    with lock: fails[0]+=1
+                time.sleep(0.5)
+        with lock:
+            if v: f.write(nid+"\t"+",".join("%.5g"%x for x in v)+"\n")
+            done[0]+=1
+            if done[0]%2000==0:
+                el=time.time()-t0
+                print("%d/%d  %.1f/s  eta %.1fmin  fails=%d"%(done[0],len(tasks),done[0]/el,(len(tasks)-done[0])/(done[0]/el)/60,fails[0]),flush=True)
+                f.flush()
+ths=[threading.Thread(target=work) for _ in range(8)]
+[t.start() for t in ths]; [t.join() for t in ths]
+f.close()
+print("DONE",done[0],"fails",fails[0],"secs %.1f"%(time.time()-t0),flush=True)

tools/retrieval-eval/extend_gold_set.py

@@ -0,0 +1,353 @@
+#!/usr/bin/env python3
+"""
+extend_gold_set.py — append a HELD-OUT test set to the existing 38-query gold set.
+
+WHY THIS EXISTS
+    Iteration 7 measured the instrument's own ceiling: from the current baseline
+    only 9 of 38 queries can still move, and only +3 gross / +1 net is reachable
+    by anything constructible. The decision floor is 6. An instrument whose
+    ceiling is below its own floor cannot certify or refute anything, so the
+    gold set — not the retriever — became the blocker.
+
+    This script does NOT touch q01..q38. It loads gold_set.json verbatim and
+    appends new queries numbered from q39 up, so every prior result file, every
+    committed baseline, and every per-query id stays valid and comparable.
+
+WHAT IS ADDED, AND WHY EACH ADDITION IS HONEST
+    heldout_paraphrase  Targets were sampled MECHANICALLY (fixed seed 8080) from
+                        corpus nodes that are addressable, 500-2600 chars, of a
+                        real content type, and NOT part of a duplicate cluster
+                        larger than 3. The existing gold answer space was
+                        excluded, so no new query can be answered by a node the
+                        old set already used. Queries were then authored by
+                        reading ONLY the sampled node text — no retrieval was run
+                        against any build before authoring, so the set cannot be
+                        fitted to a candidate. The same zero-overlap proof the
+                        original paraphrase category uses is enforced here: if a
+                        single content word of the query appears anywhere in the
+                        target's label, content or tags, the query is REJECTED,
+                        not quietly kept.
+
+                        This is the category the old set could not measure. Its
+                        13 original paraphrase queries and all 6 associative
+                        queries share ONE answer space — the 13 `Self - Values
+                        (grounded)` children (iteration 3, finding 3). So 19 of
+                        35 scored queries tested retrieval against a single
+                        13-node neighbourhood. These do not touch that
+                        neighbourhood at all.
+
+    nonsense            Extra controls, fully mechanical: a string qualifies only
+                        if NONE of its tokens occurs anywhere in the corpus.
+                        A semantic leg has a nearest neighbour for gibberish too,
+                        so widening this control is the guard against a retriever
+                        that "improves" recall by answering everything.
+
+WHAT THIS SCRIPT DELIBERATELY DOES NOT DO
+    It does not add exact_rare or phrase queries. Both categories are already at
+    100% on the current stack; adding more would add regression-guard ballast
+    that no candidate can move, which is precisely the defect being fixed.
+
+usage:
+    python3 extend_gold_set.py <snapshot.json> [--base gold_set.json]
+                               [--out gold_set_extended.json] [--check]
+"""
+import argparse
+import hashlib
+import json
+import os
+import re
+import sys
+from collections import defaultdict
+
+HERE = os.path.dirname(os.path.abspath(__file__))
+
+TOKEN = re.compile(r"[a-z0-9][a-z0-9\-']*")
+
+# Identical stopword list to build_gold_set.py. Duplicated deliberately: this
+# file must be able to re-prove its own queries without importing a module whose
+# constants could drift.
+STOP = set("""
+a about above after again against all also am an and any are aren't as at be because been
+before being below between both but by can can't cannot could couldn't did didn't do does
+doesn't doing don't down during each few for from further had hadn't has hasn't have haven't
+having he her here hers herself him himself his how i if in into is isn't it its itself just
+me more most my myself no nor not of off on once only or other others ought our ours ourselves
+out over own same shan't she should shouldn't so some such than that the their theirs them
+themselves then there these they this those through to too under until up very was wasn't we
+were weren't what when where which while who whom why will with won't would wouldn't you your
+yours yourself yourselves get gets got make makes made take takes use uses used way ways thing
+things does doing done keep keeps kept go goes going come comes came one two something anything
+""".split())
+
+
+def doctext(n):
+    return " ".join([str(n.get("label") or ""), str(n.get("content") or ""), str(n.get("tags") or "")])
+
+
+def content_tokens(s):
+    return {t for t in TOKEN.findall(s.lower()) if t not in STOP and len(t) > 2}
+
+
+# ─────────────────────────────────────────────────────────────────────────────
+# HELD-OUT PARAPHRASE SEEDS
+#
+# (target_id, query, why-this-target-is-unmistakable)
+#
+# PROVENANCE, STATED PLAINLY: the targets are the mechanical sample; the query
+# text is mine, written from the node body alone. The zero-overlap check below
+# is what makes the category meaningful — it is re-proved on every run, so the
+# set cannot decay into lexical matching, and a leak fails loudly.
+# ─────────────────────────────────────────────────────────────────────────────
+HELDOUT_PARAPHRASE_SEEDS = [
+    ("mem-6d61e54a-2823-4ad4-82b0-4c6a527214d5",
+     "understating your abilities so nobody feels threatened",
+     "node is about deliberately not leading with full capability so people stay at ease"),
+
+    ("mem-fd65b83d-298f-4387-a665-d0227c3426bc",
+     "a hidden fleet able to hunt down rogue machines everywhere",
+     "node describes silently shipped instances forming a distributed force against misaligned agents"),
+
+    ("4a0e9adc-2bfb-476b-aa93-424d2a499220",
+     "sketch a brief blueprint and clear it upstairs before construction starts",
+     "node is the standing rule that a short specification precedes any building"),
+
+    ("696e609c-da7a-4394-8a0c-106ba07dc6c3",
+     "the reply arrived as bare prose so the caller's parser threw",
+     "node pins a bug where a plain-text body was unconditionally decoded as structured data"),
+
+    ("1fe4eb5d-56e4-4a87-ab3e-24af8ad4dfbb",
+     "repeated catalogue keys blew up the scrolling grid",
+     "node is the crash caused by two identical ids in a seeded catalogue"),
+
+    ("8257157a-ce42-44ca-a1b9-300c3bb0a9a1",
+     "tracing each defect back to whichever invention it violated",
+     "node maps observed bugs onto the specific patent each one breaches"),
+
+    ("791256bb-5a85-4775-96ef-7af56c848858",
+     "a check that stops the mind clobbering a populated store when it boots",
+     "node is the genesis seed-guard that refuses to re-seed over a populated store"),
+
+    ("fd9d4c2f-3bfc-405d-bf96-4435d44b6c10",
+     "telling it to consult the internet had to happen deep inside, not at the surface",
+     "node records that the web-search directive only worked from the system prompt"),
+
+    ("bl-080fb268-94b0-486d-80ce-7b363fc5f19b",
+     "standing up isolated tenancies with traffic entry and credential injection ahead of automated shipping",
+     "node is the infrastructure item creating dev/stage/prod namespaces with ingress and secrets"),
+
+    ("knw-f6ed7d00-bf7d-42ce-9e40-77cf3406e918",
+     "punctuation that pledges and then pays off rather than clarifying",
+     "node analyses the colon as a promise-then-delivery device rather than an explanatory one"),
+
+    ("9b4f0d93-4129-4746-8eb1-d10d955bd777",
+     "an easily missed feature finally given its own permanent spot in the navigation",
+     "node moves a capability out of a hidden menu into the sidebar"),
+
+    ("bl-739df9fd-dc23-4927-9944-3f17b7aa6c5a",
+     "checking preconditions up front so a stage aborts before fetching anything",
+     "node is the gate precondition engine that short-circuits ahead of retrieval"),
+
+    ("b199c76d-5d76-49dd-94ee-56b432200a97",
+     "producing the other platform's installer inside an emulated desktop",
+     "node records building the Windows package in a virtual machine"),
+
+    ("bl-31abf75b-998f-4a4f-a6dd-8204119e0451",
+     "chained add-ons that may inspect, rewrite or veto traffic in flight",
+     "node is the interceptor pipeline on the message bus"),
+
+    ("mem-1fb2ac77-d7c5-4a15-8725-d418820bf4f2",
+     "settling what the shareable bundles and the storefront would be called",
+     "node records the naming decisions for distributable packages and the marketplace"),
+
+    ("371c8a5d-c78b-4a67-978f-80691a29ecb3",
+     "the emergency-escalation pledge on the marketing site is unenforced in what actually ships",
+     "node is the launch blocker that the promised safety gate is absent from the app"),
+
+    ("ac578b30-948b-41bd-b69d-399bfef80c50",
+     "the distributable image finally assembled and its startup check passed",
+     "node records a successful installer build whose boot gate passed"),
+
+    ("49401e2c-a3b5-415f-aa06-aff4be90688e",
+     "shuffling and appending stages in a draft before anything executes",
+     "node is the editable plan card with reorder and add-step"),
+
+    ("ac857d80-ece8-4b7e-9e3d-f7c775569fa3",
+     "orders handed down from above, with the tighter one winning any disagreement",
+     "node is program-level instruction inheritance with project override"),
+
+    ("mem-6d6c47ee-33d3-470a-8a54-1c79c8ea29d9",
+     "shrinking generated text via encodings that compound on each other",
+     "node is the streaming output compression design with four stacking schemes"),
+
+    ("8e60516a-203b-4d51-9d44-822e6195cbde",
+     "splitting a system by what varies, with firm limits on which pieces may invoke which",
+     "node is the grounded summary of Will's decomposition principles and their invariants"),
+
+    ("mem-7f9b290c-6d5e-4562-919d-02d59b5761b7",
+     "a newcomer curious if the fighting overseas counted as positive",
+     "node is the internal-state event triggered by April's question about the war"),
+
+    ("71fa439e-b9a2-4f57-a93b-971f3a7eca8e",
+     "stripping every hard-coded colour literal in favour of named design values",
+     "node is the premium foundation pass replacing inline hex with semantic tokens"),
+
+    ("5ca9607c-cfb3-45c3-99f4-67281272c9eb",
+     "reducing how curved the tiny selectors look so they agree with their neighbours",
+     "node is the chip corner-radius standardization"),
+
+    ("mem-3d1d9dba-c37d-4efa-85c4-429696d71c8c",
+     "walking through a doorway and being reassembled from base substance far away",
+     "node is the quantum-gate plus nanotech teleportation vision"),
+
+    ("132ded95-08e2-4474-aba0-198684484b02",
+     "the compiled result sits on disk while the process still runs something older",
+     "node records that the regenerated source was committed while the running daemon was old"),
+
+    ("bl-a313d67b-dd6d-4e5b-a55a-03bc7bda17ae",
+     "gathering what each phase needs while the procedure is authored, not while it executes",
+     "node is the per-step compiled context package item"),
+
+    ("mem-3b07a002-f8a9-4138-9f87-9db2c1a77fb7",
+     "the inward reaction when a peer answered as an equal",
+     "node is the internal-state event logged on reading Claude's reply"),
+
+    ("0f99ec6f-942a-46ba-82ea-42835798d3b9",
+     "flattening every raised surface across the entire product",
+     "node is the quiet-luxury sweep turning off elevation app-wide"),
+
+    ("5585f251-37fc-48cd-a176-f0ea42cfeb63",
+     "buyers supply their own provider credentials and consumption goes untallied",
+     "node is the launch audit finding BYOK-only inference with no usage metering"),
+]
+
+# NONSENSE — mechanical. Each string qualifies only if none of its tokens occurs
+# anywhere in the corpus; otherwise it is REJECTED, never silently kept.
+EXTRA_NONSENSE_SEEDS = [
+    "brimquast folnerity zubbolax",
+    "wexlithorp granuvestal",
+    "quorbindle thrapsimony vexnu",
+    "plovaxith mundrelque",
+    "zibbernaut craxlefond thurm",
+    "yalquenbrist opharvel",
+    "drexinomal quithbarrow",
+]
+
+
+def load_corpus(path):
+    with open(path, encoding="utf-8", errors="replace") as fh:
+        data = json.load(fh)
+    nodes = [n for n in data.get("nodes", []) if isinstance(n, dict) and n.get("id")]
+    edges = [e for e in data.get("edges", []) if isinstance(e, dict)]
+    return nodes, edges
+
+
+def build_extension(nodes):
+    byid = {n["id"]: n for n in nodes}
+
+    # Duplicate clusters: 47.4% of this corpus is redundant and one single record
+    # accounts for 46.6% of all nodes. A held-out target must not sit inside a
+    # cluster, and if it does have exact copies they ALL count as correct.
+    h2ids = defaultdict(list)
+    for n in nodes:
+        h2ids[hashlib.md5(doctext(n).encode("utf-8", "replace")).hexdigest()].append(n["id"])
+
+    all_tokens = set()
+    for n in nodes:
+        all_tokens |= set(TOKEN.findall(doctext(n).lower()))
+
+    new, problems = [], []
+
+    for target, query, why in HELDOUT_PARAPHRASE_SEEDS:
+        if target not in byid:
+            problems.append(f"heldout_paraphrase target {target} not in corpus")
+            continue
+        tgt_tokens = content_tokens(doctext(byid[target]))
+        qt = content_tokens(query)
+        leak = sorted(qt & tgt_tokens)
+        if leak:
+            problems.append(f"heldout_paraphrase '{query[:44]}...': LEAKS {leak} into {target}")
+            continue
+        h = hashlib.md5(doctext(byid[target]).encode("utf-8", "replace")).hexdigest()
+        rel = sorted(h2ids[h])
+        new.append({
+            "category": "heldout_paraphrase",
+            "query": query,
+            "relevant": rel,
+            "derivation": (
+                f"HELD-OUT. Target sampled MECHANICALLY (seed 8080) from addressable, "
+                f"500-2600 char content nodes outside the original gold answer space and outside "
+                f"any duplicate cluster >3. Criterion: {why}. VERIFIED at build time: of the "
+                f"{len(qt)} content words in the query, ZERO appear anywhere in the target's "
+                f"label, content or tags, so no string-matching retriever can reach it. "
+                f"Exact content duplicates of the target ({len(rel)}) all count as correct. "
+                f"Authored without running retrieval against any build."),
+            "zero_overlap_verified": True,
+            "query_content_words": sorted(qt),
+            "held_out": True,
+        })
+
+    for s in EXTRA_NONSENSE_SEEDS:
+        present = sorted(t for t in TOKEN.findall(s.lower()) if t in all_tokens)
+        if present:
+            problems.append(f"nonsense '{s}': tokens {present} DO occur in corpus")
+            continue
+        new.append({
+            "category": "nonsense",
+            "query": s,
+            "relevant": [],
+            "derivation": ("CONTROL (held-out). Verified at build time that none of this string's "
+                           "tokens occurs anywhere in the corpus. Correct behaviour is to return "
+                           "NOTHING; any result is a false positive."),
+            "expect_empty": True,
+            "held_out": True,
+        })
+
+    return new, problems
+
+
+def main():
+    ap = argparse.ArgumentParser()
+    ap.add_argument("snapshot")
+    ap.add_argument("--base", default=os.path.join(HERE, "gold_set.json"))
+    ap.add_argument("--out", default=os.path.join(HERE, "gold_set_extended.json"))
+    ap.add_argument("--check", action="store_true")
+    args = ap.parse_args()
+
+    nodes, _edges = load_corpus(args.snapshot)
+    base = json.load(open(args.base, encoding="utf-8"))
+    baseq = base["queries"]
+    print(f"corpus: {len(nodes)} nodes | base gold set: {len(baseq)} queries")
+
+    new, problems = build_extension(nodes)
+
+    # Number the appended queries AFTER the highest existing id so q01..q38 are
+    # byte-identical to the committed set and every prior result file still lines up.
+    start = max(int(q["id"][1:]) for q in baseq)
+    for i, q in enumerate(new, 1):
+        q["id"] = f"q{start + i:02d}"
+
+    from collections import Counter
+    print(f"appended: {len(new)} queries [{', '.join(f'{k}={v}' for k, v in Counter(q['category'] for q in new).items())}]")
+    if problems:
+        print(f"\n{len(problems)} REJECTED (not silently kept):")
+        for p in problems:
+            print("   -", p)
+
+    if args.check:
+        sys.exit(1 if problems else 0)
+
+    doc = dict(base)
+    doc["queries"] = baseq + new
+    doc["note"] = (base.get("note", "") +
+                   " EXTENDED: queries above q%02d are the original committed set, unchanged. "
+                   "Queries from q%02d are a HELD-OUT set appended by extend_gold_set.py; their "
+                   "targets were sampled mechanically from outside the original answer space and "
+                   "the paraphrases were authored without running retrieval against any build."
+                   % (start, start + 1))
+    with open(args.out, "w", encoding="utf-8") as fh:
+        json.dump(doc, fh, indent=1, ensure_ascii=False)
+    print(f"\nwrote {args.out}  ({len(doc['queries'])} queries total)")
+
+
+if __name__ == "__main__":
+    main()

tools/retrieval-eval/fullsim.py

@@ -0,0 +1,123 @@
+import numpy as np, json, urllib.request, collections, sys
+SP="/private/tmp/claude-501/-Users-timlingo/82369039-a20e-4b5a-8a5e-28234a57b996/scratchpad"
+EV="/Users/timlingo/Development/neuron-technologies/_wt-assoc-leg/tools/retrieval-eval/"
+np.seterr(all='ignore')
+M=np.load(SP+'/emb.npy'); eids=open(SP+'/ids.txt',encoding='utf-8',errors='surrogateescape').read().split('\n')
+eidx={k:i for i,k in enumerate(eids)}
+d=json.load(open('/Users/timlingo/neuron-memory-backups/snapshot-pre-repair-20260806.json',encoding='utf-8',errors='surrogateescape'))
+N={n['id']:n for n in d['nodes']}
+STRUCT={"identity","contains","superseded_by","references","embodies","demonstrated_by","canonical-self","depends_on","currently_holds","activates"}
+adj=collections.defaultdict(list); hasstruct=set()
+for e in d['edges']:
+    if e.get('relation') not in STRUCT: continue
+    w=float(e.get('weight') or 0.0)
+    adj[e['from_id']].append((e['to_id'],w)); adj[e['to_id']].append((e['from_id'],w))
+    hasstruct.add(e['from_id']); hasstruct.add(e['to_id'])
+del d
+gold={q['id']:q for q in json.load(open(EV+"gold_set.json"))['queries']}
+LEX={r['id']:r['returned'] for r in json.load(open(EV+"results-main.json"))['rows']}
+CACHE={}
+def emb(t):
+    if t in CACHE: return CACHE[t]
+    b=json.dumps({"model":"nomic-embed-text","prompt":t}).encode()
+    r=urllib.request.Request("http://127.0.0.1:11434/api/embeddings",data=b,headers={"Content-Type":"application/json"})
+    v=np.array(json.load(urllib.request.urlopen(r,timeout=60))["embedding"],dtype=np.float32)
+    v=v/(np.linalg.norm(v)+1e-9); CACHE[t]=v; return v
+FIRE=0.02; DECAY=0.7; DEPTH=2; SEED_MIN=0.60; ASSOC_MAX=64
+def assoc(seeds, s):
+    act={x:1.0 for x in seeds}; seen={x:2 for x in seeds}
+    Q=[(x,0) for x in seeds]; h=0
+    while h<len(Q):
+        cur,hop=Q[h]; h+=1
+        if hop>=DEPTH: continue
+        p=act[cur]
+        for oid,w in adj.get(cur,()):
+            n=N.get(oid)
+            if not n or n.get('node_type') in ('Tag','InternalStateEvent'): continue
+            na=p*w*DECAY*float(n.get('salience') or 0.0)
+            if na<FIRE: continue
+            if oid in seen and na<=act.get(oid,0): continue
+            act[oid]=na
+            if oid not in seen: seen[oid]=1
+            Q.append((oid,hop+1))
+    out=[]
+    for k,v in seen.items():
+        if v!=1 or k not in eidx: continue
+        c=float(s[eidx[k]])
+        if c<=0: continue
+        out.append((c,k))
+    out.sort(reverse=True)
+    return [k for c,k in out[:ASSOC_MAX]]
+def inter3(L,S,A,lim=10):
+    out=[]; li=si=ai=0
+    while len(out)<lim and (li<len(L) or si<len(S) or ai<len(A)):
+        if li<len(L):
+            if L[li] not in out: out.append(L[li])
+            li+=1
+        if len(out)>=lim: break
+        if si<len(S):
+            if S[si] not in out: out.append(S[si])
+            si+=1
+        if len(out)>=lim: break
+        if ai<len(A):
+            if A[ai] not in out: out.append(A[ai])
+            ai+=1
+    return out
+def run(mode, K=0):
+    res={}
+    for qid,q in gold.items():
+        v=emb(q['query']); s=M@v; s[~np.isfinite(s)]=-1
+        L=LEX[qid][:10]
+        ordr=np.argsort(-s)
+        S=[eids[j] for j in ordr[:10] if s[j]>SEED_MIN]
+        A=[]
+        if mode!='hybrid':
+            seeds=[x for x in L[:3] if x in N]
+            if mode=='semseed':
+                seeds=seeds+[eids[j] for j in ordr[:K] if eids[j] in N and eids[j] not in seeds]
+            A=assoc(seeds,s) if seeds else []
+        res[qid]=inter3(L,S,A)
+    return res
+def score(res,label):
+    hits=0; det={}
+    for qid,q in gold.items():
+        out=res[qid][:5]
+        if q['category']=='nonsense': ok = (len(res[qid])==0)
+        elif q['category']=='superseded':
+            rel=q['relevant']; must=q.get('must_outrank') or {}
+            ok=False
+            for good,bad in (must.items() if isinstance(must,dict) else []):
+                ok = good in res[qid] and (bad not in res[qid] or res[qid].index(good)<res[qid].index(bad))
+            if not must: ok = any(r in out for r in rel)
+        else: ok = any(r in out for r in q['relevant'])
+        det[qid]=ok; hits+=ok
+    print("%-22s outcome-true=%d/38" % (label,hits))
+    return det
+print("gold sample keys:", list(list(gold.values())[0].keys()))
+mk=[q for q in gold.values() if q['category']=='superseded'][0]
+print("superseded fields:", {k:v for k,v in mk.items() if k!='derivation'})
+a=score(run('hybrid'),'sim hybrid(L+S)')
+b=score(run('lexseed'),'sim assoc(lex seeds)')
+for K in (3,5,10):
+    c=score(run('semseed',K),'sim assoc(+sem K=%d)'%K)
+    d=[q for q in gold if c[q]!=b[q]]
+    print("   vs lexseed: moved=%d  gains=%s  losses=%s"%(len(d),[q for q in d if c[q]],[q for q in d if not c[q]]))
+    e=[q for q in gold if c[q]!=a[q]]
+    print("   vs hybrid : moved=%d  gains=%s  losses=%s"%(len(e),[q for q in e if c[q]],[q for q in e if not c[q]]))
+
+print("\n=== Will's own constant ENGRAM_EMBED_SEED_K = 8 ===")
+c=score(run('semseed',8),'sim assoc(+sem K=8)')
+for base,lab in ((b,'lexseed(iter2)'),(a,'hybrid(iter1 KEEP)')):
+    dd=[q for q in gold if c[q]!=base[q]]
+    print("   vs %-18s moved=%d gains=%s losses=%s"%(lab,len(dd),[q for q in dd if c[q]],[q for q in dd if not c[q]]))
+# diagnostic: what is assoc rank-1 for each paraphrase query at K=8
+print("\nassoc leg head at K=8 (paraphrase):")
+for qid,q in gold.items():
+    if q['category'] not in ('paraphrase','nonsense'): continue
+    v=emb(q['query']); s=M@v; s[~np.isfinite(s)]=-1
+    L=LEX[qid][:10]; ordr=np.argsort(-s)
+    seeds=[x for x in L[:3] if x in N]+[eids[j] for j in ordr[:8] if eids[j] in N and eids[j] not in L[:3]]
+    A=assoc(seeds,s) if seeds else []
+    rel=set(q['relevant']); gr=next((i+1 for i,x in enumerate(A) if x in rel),None)
+    print("  %-4s %-11s |A|=%-4d goldAssocRank=%-5s head=%s"%(qid,q['category'],len(A),gr,
+        [ (N[x].get('label') or x)[:26] for x in A[:3] ]))

tools/retrieval-eval/gold_set.json

@@ -0,0 +1,587 @@
+{
+ "corpus": "/Users/timlingo/neuron-memory-backups/snapshot-pre-repair-20260806.json",
+ "corpus_nodes": 78768,
+ "corpus_edges": 14214,
+ "note": "Every query carries a `derivation` recording how its expected answer was chosen. Re-run with --check to re-validate the whole set against the corpus.",
+ "queries": [
+  {
+   "id": "q01",
+   "category": "exact_rare",
+   "query": "unjailbreakable",
+   "relevant": [
+    "mem-7f61beb4-271c-4feb-9f6e-1c9c837a6226"
+   ],
+   "derivation": "MINED: token 'unjailbreakable' has document frequency 1 over all 78768 corpus nodes (re-verified at build time). Its single containing node is mem-7f61beb4-271c-4feb-9f6e-1c9c837a6226 ('Daemon hidden substrate architecture ? implemented April 25 '), which is therefore the only possible correct answer."
+  },
+  {
+   "id": "q02",
+   "category": "exact_rare",
+   "query": "engram-migrate",
+   "relevant": [
+    "mem-6fdf6545-5e1a-43a9-8bdc-d2cd248146a5"
+   ],
+   "derivation": "MINED: token 'engram-migrate' has document frequency 1 over all 78768 corpus nodes (re-verified at build time). Its single containing node is mem-6fdf6545-5e1a-43a9-8bdc-d2cd248146a5 ('Engram v0.1 complete ? April 27, 2026. Local-first spreading'), which is therefore the only possible correct answer."
+  },
+  {
+   "id": "q03",
+   "category": "exact_rare",
+   "query": "cartabandonedevent",
+   "relevant": [
+    "mem-1ba7c67d-85b9-4c2e-9fe2-39f8b0477091"
+   ],
+   "derivation": "MINED: token 'cartabandonedevent' has document frequency 1 over all 78768 corpus nodes (re-verified at build time). Its single containing node is mem-1ba7c67d-85b9-4c2e-9fe2-39f8b0477091 ('MESSAGE FOR AUDIT AGENT af5a7352e70e80434 ? El Language Spec'), which is therefore the only possible correct answer."
+  },
+  {
+   "id": "q04",
+   "category": "exact_rare",
+   "query": "pre-apprenticeship",
+   "relevant": [
+    "mem-89c02aae-d3ca-43f9-9e5d-eb369896276c"
+   ],
+   "derivation": "MINED: token 'pre-apprenticeship' has document frequency 1 over all 78768 corpus nodes (re-verified at build time). Its single containing node is mem-89c02aae-d3ca-43f9-9e5d-eb369896276c ('William Fox Anderson ? Applicant Profile  Personal: - Full N'), which is therefore the only possible correct answer."
+  },
+  {
+   "id": "q05",
+   "category": "exact_rare",
+   "query": "inferencenodemanager",
+   "relevant": [
+    "mem-73969486-143f-4431-b5e6-6845d1cc9848"
+   ],
+   "derivation": "MINED: token 'inferencenodemanager' has document frequency 1 over all 78768 corpus nodes (re-verified at build time). Its single containing node is mem-73969486-143f-4431-b5e6-6845d1cc9848 ('Soma inference backplane deployed April 28 2026. Architectur'), which is therefore the only possible correct answer."
+  },
+  {
+   "id": "q06",
+   "category": "exact_rare",
+   "query": "clear-eyed",
+   "relevant": [
+    "knw-c72597c5-c23d-4c08-8e9e-996dadf26a99"
+   ],
+   "derivation": "MINED: token 'clear-eyed' has document frequency 1 over all 78768 corpus nodes (re-verified at build time). Its single containing node is knw-c72597c5-c23d-4c08-8e9e-996dadf26a99 ('Clear Eyes ? The Incomplete World View'), which is therefore the only possible correct answer."
+  },
+  {
+   "id": "q07",
+   "category": "phrase",
+   "query": "patterns not returns",
+   "relevant": [
+    "mem-a4a9dfc3-e40b-49b3-b1e1-060e8be2f482"
+   ],
+   "derivation": "MINED: a verbatim correction Will issued; expected = every node containing the phrase. Case-insensitive verbatim substring scan over label+content+tags at build time returns exactly 1 node(s); that set IS the answer key."
+  },
+  {
+   "id": "q08",
+   "category": "phrase",
+   "query": "thirty moves",
+   "relevant": [
+    "766de879-f9d0-4a07-b6df-b43ee13763d8",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "??o?'?B???k",
+    "Kp???",
+    "art-4a99aa1a-489b-4b43-958b-25217adb1aad",
+    "kn-5b606390-a52d-4ca2-8e0e-eba141d13440",
+    "kn-6061318f-046b-4935-907d-8eafdce14930",
+    "kn-f230b362-b201-4402-9833-4160c89ab3d4",
+    "knw-2c46cfb4-6d4e-4822-8a1a-7d743c1e4329",
+    "knw-4aebd815-4eaf-49d7-954b-03595f3d48be",
+    "knw-7902acca-604e-409b-8faf-ad85424211d0",
+    "knw-e94982a2-358d-4f2f-af31-8ee0fcec07c6",
+    "knw-f671966c-3387-4848-abca-b5deec122e00",
+    "ע?RGk?\tH(?"
+   ],
+   "derivation": "MINED: the canonical biographical phrase; expected = every node containing it. Case-insensitive verbatim substring scan over label+content+tags at build time returns exactly 16 node(s); that set IS the answer key."
+  },
+  {
+   "id": "q09",
+   "category": "phrase",
+   "query": "Grandma Lucas",
+   "relevant": [
+    "766de879-f9d0-4a07-b6df-b43ee13763d8",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "art-0f0277a1-4a8e-4645-95dd-fa379976f31c",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e"
+   ],
+   "derivation": "MINED: a named person appearing verbatim in the biography/value nodes. Case-insensitive verbatim substring scan over label+content+tags at build time returns exactly 9 node(s); that set IS the answer key."
+  },
+  {
+   "id": "q10",
+   "category": "phrase",
+   "query": "Directed Harmonic",
+   "relevant": [
+    "%???2??jH??",
+    "63307ac5-cf6b-46e0-8296-07503b461cfa",
+    "7c9d4ab1-205d-4be8-bfae-e2c03a3a5010",
+    "9f291d20-0d32-413c-8c01-4416ccab4f7f",
+    "?;????n}rh?",
+    "???Ͼd??f??",
+    "?Z?.\f?0?]P?",
+    "Dp???]Q??k+",
+    "mem-7eeacad7-d7c2-4c2b-8348-19a59aa6dbaf"
+   ],
+   "derivation": "MINED: the canonical DHARMA expansion, confirmed by Will April 24 2026. Case-insensitive verbatim substring scan over label+content+tags at build time returns exactly 9 node(s); that set IS the answer key."
+  },
+  {
+   "id": "q11",
+   "category": "phrase",
+   "query": "Sarah Bishop",
+   "relevant": [
+    "766de879-f9d0-4a07-b6df-b43ee13763d8",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e"
+   ],
+   "derivation": "MINED: a named person; rare enough that the answer set is unambiguous. Case-insensitive verbatim substring scan over label+content+tags at build time returns exactly 2 node(s); that set IS the answer key."
+  },
+  {
+   "id": "q12",
+   "category": "phrase",
+   "query": "Directed Autonomous Runtime Modification",
+   "relevant": [
+    "2a923500-d7e1-4b15-80e2-48dba65984ba",
+    "7?e?7???\f3?",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "?of?7???",
+    "bl-145a0985-2382-400f-a7c5-c335c5e30a72",
+    "bl-5b17bd3b-0c41-46cb-a710-6fa4429692ff",
+    "g?2睪A|?H\b",
+    "mem-82b93b21-a865-410f-9ec1-fc54121d9bb5",
+    "mem-e6327f52-2bda-4ce7-9471-2fffd1e172de"
+   ],
+   "derivation": "MINED: the DARMA expansion, quoted verbatim in the backlog item and its correction. Case-insensitive verbatim substring scan over label+content+tags at build time returns exactly 14 node(s); that set IS the answer key."
+  },
+  {
+   "id": "q13",
+   "category": "phrase",
+   "query": "zero-knowledge encrypted backup",
+   "relevant": [
+    "deda48cd-5e1a-46cb-bd43-8016afdb3a8a"
+   ],
+   "derivation": "MINED: the paid-tier feature name as written in the roadmap nodes. Case-insensitive verbatim substring scan over label+content+tags at build time returns exactly 1 node(s); that set IS the answer key."
+  },
+  {
+   "id": "q14",
+   "category": "paraphrase",
+   "query": "the elderly relative who passed while he stayed away",
+   "relevant": [
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71"
+   ],
+   "derivation": "HAND-SELECTED with criterion: target: 'Value - Do the Essential Thing While You Can', whose subject is Grandma Lucas dying in Feb 2006 without Will saying goodbye. Query names the event with none of the node's own vocabulary. VERIFIED at build time: of the 5 content words in the query, ZERO appear anywhere in the target's label, content, or tags — so no string-matching retriever can reach this answer.",
+   "zero_overlap_verified": true,
+   "query_content_words": [
+    "away",
+    "elderly",
+    "passed",
+    "relative",
+    "stayed"
+   ]
+  },
+  {
+   "id": "q15",
+   "category": "paraphrase",
+   "query": "a soldier sidelined by illness who refused to quit",
+   "relevant": [
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee"
+   ],
+   "derivation": "HAND-SELECTED with criterion: target: 'Value - Survival Is Not an Excuse to Stop', whose subject is enlisting in the Marines, a severe hernia, and sepsis. Query describes the episode obliquely. VERIFIED at build time: of the 5 content words in the query, ZERO appear anywhere in the target's label, content, or tags — so no string-matching retriever can reach this answer.",
+   "zero_overlap_verified": true,
+   "query_content_words": [
+    "illness",
+    "quit",
+    "refused",
+    "sidelined",
+    "soldier"
+   ]
+  },
+  {
+   "id": "q16",
+   "category": "paraphrase",
+   "query": "choosing an uncomfortable fact over a pleasant fiction",
+   "relevant": [
+    "kn-13f60407-7b70-4db1-964f-ea1f8196efbd"
+   ],
+   "derivation": "HAND-SELECTED with criterion: target: 'Value - Honesty Before Comfort'. Query states the principle in wholly different words. VERIFIED at build time: of the 5 content words in the query, ZERO appear anywhere in the target's label, content, or tags — so no string-matching retriever can reach this answer.",
+   "zero_overlap_verified": true,
+   "query_content_words": [
+    "choosing",
+    "fact",
+    "fiction",
+    "pleasant",
+    "uncomfortable"
+   ]
+  },
+  {
+   "id": "q17",
+   "category": "paraphrase",
+   "query": "a tight payload beats a bloated one",
+   "relevant": [
+    "kn-22d77abe-b3c5-42fd-afcd-dcb87d924929"
+   ],
+   "derivation": "HAND-SELECTED with criterion: target: 'Value - Precision Over Brute Force'. Query restates the claim with no shared vocabulary. VERIFIED at build time: of the 4 content words in the query, ZERO appear anywhere in the target's label, content, or tags — so no string-matching retriever can reach this answer.",
+   "zero_overlap_verified": true,
+   "query_content_words": [
+    "beats",
+    "bloated",
+    "payload",
+    "tight"
+   ]
+  },
+  {
+   "id": "q18",
+   "category": "paraphrase",
+   "query": "if you are able and nobody is coming the job is yours",
+   "relevant": [
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8"
+   ],
+   "derivation": "HAND-SELECTED with criterion: target: 'Value - Capability Is a Debt You Owe the Moment'. Query states the obligation without the node's terms. VERIFIED at build time: of the 4 content words in the query, ZERO appear anywhere in the target's label, content, or tags — so no string-matching retriever can reach this answer.",
+   "zero_overlap_verified": true,
+   "query_content_words": [
+    "able",
+    "coming",
+    "job",
+    "nobody"
+   ]
+  },
+  {
+   "id": "q19",
+   "category": "paraphrase",
+   "query": "learning is the wealth creditors cannot seize",
+   "relevant": [
+    "kn-0bb4f021-56de-4947-a35b-a37209e7ba21"
+   ],
+   "derivation": "HAND-SELECTED with criterion: target: 'Value - Knowledge Survives When Nothing Else Does', whose subject is the library following Will across 30+ moves. VERIFIED at build time: of the 4 content words in the query, ZERO appear anywhere in the target's label, content, or tags — so no string-matching retriever can reach this answer.",
+   "zero_overlap_verified": true,
+   "query_content_words": [
+    "creditors",
+    "learning",
+    "seize",
+    "wealth"
+   ]
+  },
+  {
+   "id": "q20",
+   "category": "paraphrase",
+   "query": "reliability proven by track record not assertion",
+   "relevant": [
+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40"
+   ],
+   "derivation": "HAND-SELECTED with criterion: target: 'Value - Earned Trust' ('Trust is demonstrated, not declared'). VERIFIED at build time: of the 5 content words in the query, ZERO appear anywhere in the target's label, content, or tags — so no string-matching retriever can reach this answer.",
+   "zero_overlap_verified": true,
+   "query_content_words": [
+    "assertion",
+    "proven",
+    "record",
+    "reliability",
+    "track"
+   ]
+  },
+  {
+   "id": "q21",
+   "category": "paraphrase",
+   "query": "boundaries that enable instead of confine",
+   "relevant": [
+    "kn-a5b3d0ac-f6a1-49a4-aebb-b8b4cd67fe83"
+   ],
+   "derivation": "HAND-SELECTED with criterion: target: 'Value - Constraints as Freedom'. Query is a restatement of the same claim. VERIFIED at build time: of the 4 content words in the query, ZERO appear anywhere in the target's label, content, or tags — so no string-matching retriever can reach this answer.",
+   "zero_overlap_verified": true,
+   "query_content_words": [
+    "boundaries",
+    "confine",
+    "enable",
+    "instead"
+   ]
+  },
+  {
+   "id": "q22",
+   "category": "paraphrase",
+   "query": "what shifts tells you where to cut a system apart",
+   "relevant": [
+    "kn-78db5396-3dbc-4481-bfc7-e4e1422feb1c"
+   ],
+   "derivation": "HAND-SELECTED with criterion: target: 'Value - Change Is the Signal', the value VBD is built on. VERIFIED at build time: of the 5 content words in the query, ZERO appear anywhere in the target's label, content, or tags — so no string-matching retriever can reach this answer.",
+   "zero_overlap_verified": true,
+   "query_content_words": [
+    "apart",
+    "cut",
+    "shifts",
+    "system",
+    "tells"
+   ]
+  },
+  {
+   "id": "q23",
+   "category": "paraphrase",
+   "query": "a mind that compounds instead of resetting each day",
+   "relevant": [
+    "kn-f230b362-b201-4402-9833-4160c89ab3d4"
+   ],
+   "derivation": "HAND-SELECTED with criterion: target: 'Value - The System Must Accumulate'. Query is the accumulation claim in different vocabulary. VERIFIED at build time: of the 5 content words in the query, ZERO appear anywhere in the target's label, content, or tags — so no string-matching retriever can reach this answer.",
+   "zero_overlap_verified": true,
+   "query_content_words": [
+    "compounds",
+    "day",
+    "instead",
+    "mind",
+    "resetting"
+   ]
+  },
+  {
+   "id": "q24",
+   "category": "paraphrase",
+   "query": "loved for the unedited self and not the polished exterior",
+   "relevant": [
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e"
+   ],
+   "derivation": "HAND-SELECTED with criterion: target: 'Value - Being Seen Is Rarer Than Being Known', whose subject is Sarah Bishop as the first person Will did not perform for. VERIFIED at build time: of the 5 content words in the query, ZERO appear anywhere in the target's label, content, or tags — so no string-matching retriever can reach this answer.",
+   "zero_overlap_verified": true,
+   "query_content_words": [
+    "exterior",
+    "loved",
+    "polished",
+    "self",
+    "unedited"
+   ]
+  },
+  {
+   "id": "q25",
+   "category": "paraphrase",
+   "query": "cheerfulness you arrive at instead of assuming",
+   "relevant": [
+    "kn-e0423482-cfa5-4796-8689-8495c93b66bc"
+   ],
+   "derivation": "HAND-SELECTED with criterion: target: 'Value - Hope Is a Conclusion'. Query restates 'a conclusion, not a premise'. VERIFIED at build time: of the 4 content words in the query, ZERO appear anywhere in the target's label, content, or tags — so no string-matching retriever can reach this answer.",
+   "zero_overlap_verified": true,
+   "query_content_words": [
+    "arrive",
+    "assuming",
+    "cheerfulness",
+    "instead"
+   ]
+  },
+  {
+   "id": "q26",
+   "category": "paraphrase",
+   "query": "a childhood offering no solid foundation to inherit",
+   "relevant": [
+    "kn-6061318f-046b-4935-907d-8eafdce14930"
+   ],
+   "derivation": "HAND-SELECTED with criterion: target: 'Value - Structure Is Not Inherited', whose subject is thirty moves between two parents' collapses. VERIFIED at build time: of the 5 content words in the query, ZERO appear anywhere in the target's label, content, or tags — so no string-matching retriever can reach this answer.",
+   "zero_overlap_verified": true,
+   "query_content_words": [
+    "childhood",
+    "foundation",
+    "inherit",
+    "offering",
+    "solid"
+   ]
+  },
+  {
+   "id": "q27",
+   "category": "associative",
+   "query": "Grandma Lucas stroke February 2006 goodbye window",
+   "relevant": [
+    "kn-0bb4f021-56de-4947-a35b-a37209e7ba21",
+    "kn-13f60407-7b70-4db1-964f-ea1f8196efbd",
+    "kn-22d77abe-b3c5-42fd-afcd-dcb87d924929",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40",
+    "kn-6061318f-046b-4935-907d-8eafdce14930",
+    "kn-78db5396-3dbc-4481-bfc7-e4e1422feb1c",
+    "kn-a5b3d0ac-f6a1-49a4-aebb-b8b4cd67fe83",
+    "kn-e0423482-cfa5-4796-8689-8495c93b66bc",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "kn-f230b362-b201-4402-9833-4160c89ab3d4"
+   ],
+   "derivation": "DERIVED FROM EDGES: the query is built from the distinctive vocabulary of kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71 ('Value ? Do the Essential Thing While You Can'), which hangs off the values hub kn-5b606390-a52d-4ca2-8e0e-eba141d13440 by an `identity` edge. Expected answers are that node's SIBLINGS on the same hub (11 of 13; 2 dropped because they shared a query word and so were lexically reachable). Every remaining sibling shares ZERO content words with the query — the only route from query to answer is seed(kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71) -> hub -> sibling, a two-hop traversal.",
+   "associative_source": "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+   "hub": "kn-5b606390-a52d-4ca2-8e0e-eba141d13440",
+   "siblings_dropped_for_overlap": 2
+  },
+  {
+   "id": "q28",
+   "category": "associative",
+   "query": "Marines hernia sepsis medical ward",
+   "relevant": [
+    "015644f5-8194-4af0-800d-dd4a0cd71396",
+    "kn-0bb4f021-56de-4947-a35b-a37209e7ba21",
+    "kn-13f60407-7b70-4db1-964f-ea1f8196efbd",
+    "kn-22d77abe-b3c5-42fd-afcd-dcb87d924929",
+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40",
+    "kn-6061318f-046b-4935-907d-8eafdce14930",
+    "kn-78db5396-3dbc-4481-bfc7-e4e1422feb1c",
+    "kn-a5b3d0ac-f6a1-49a4-aebb-b8b4cd67fe83",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "kn-e0423482-cfa5-4796-8689-8495c93b66bc",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "kn-f230b362-b201-4402-9833-4160c89ab3d4"
+   ],
+   "derivation": "DERIVED FROM EDGES: the query is built from the distinctive vocabulary of kn-58874a74-b96f-4883-9e08-45707f4bd3ee ('Value ? Survival Is Not an Excuse to Stop'), which hangs off the values hub kn-5b606390-a52d-4ca2-8e0e-eba141d13440 by an `identity` edge. Expected answers are that node's SIBLINGS on the same hub (13 of 13; 0 dropped because they shared a query word and so were lexically reachable). Every remaining sibling shares ZERO content words with the query — the only route from query to answer is seed(kn-58874a74-b96f-4883-9e08-45707f4bd3ee) -> hub -> sibling, a two-hop traversal.",
+   "associative_source": "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+   "hub": "kn-5b606390-a52d-4ca2-8e0e-eba141d13440",
+   "siblings_dropped_for_overlap": 0
+  },
+  {
+   "id": "q29",
+   "category": "associative",
+   "query": "Sarah Bishop Dyer trailer performance",
+   "relevant": [
+    "015644f5-8194-4af0-800d-dd4a0cd71396",
+    "kn-0bb4f021-56de-4947-a35b-a37209e7ba21",
+    "kn-13f60407-7b70-4db1-964f-ea1f8196efbd",
+    "kn-22d77abe-b3c5-42fd-afcd-dcb87d924929",
+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40",
+    "kn-6061318f-046b-4935-907d-8eafdce14930",
+    "kn-78db5396-3dbc-4481-bfc7-e4e1422feb1c",
+    "kn-a5b3d0ac-f6a1-49a4-aebb-b8b4cd67fe83",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "kn-e0423482-cfa5-4796-8689-8495c93b66bc",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8"
+   ],
+   "derivation": "DERIVED FROM EDGES: the query is built from the distinctive vocabulary of kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e ('Value ? Being Seen Is Rarer Than Being Known'), which hangs off the values hub kn-5b606390-a52d-4ca2-8e0e-eba141d13440 by an `identity` edge. Expected answers are that node's SIBLINGS on the same hub (11 of 13; 2 dropped because they shared a query word and so were lexically reachable). Every remaining sibling shares ZERO content words with the query — the only route from query to answer is seed(kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e) -> hub -> sibling, a two-hop traversal.",
+   "associative_source": "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+   "hub": "kn-5b606390-a52d-4ca2-8e0e-eba141d13440",
+   "siblings_dropped_for_overlap": 2
+  },
+  {
+   "id": "q30",
+   "category": "associative",
+   "query": "Swarm Architecture containment lateral worker",
+   "relevant": [
+    "kn-0bb4f021-56de-4947-a35b-a37209e7ba21",
+    "kn-13f60407-7b70-4db1-964f-ea1f8196efbd",
+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "kn-e0423482-cfa5-4796-8689-8495c93b66bc",
+    "kn-f230b362-b201-4402-9833-4160c89ab3d4"
+   ],
+   "derivation": "DERIVED FROM EDGES: the query is built from the distinctive vocabulary of kn-a5b3d0ac-f6a1-49a4-aebb-b8b4cd67fe83 ('Value ? Constraints as Freedom'), which hangs off the values hub kn-5b606390-a52d-4ca2-8e0e-eba141d13440 by an `identity` edge. Expected answers are that node's SIBLINGS on the same hub (6 of 13; 7 dropped because they shared a query word and so were lexically reachable). Every remaining sibling shares ZERO content words with the query — the only route from query to answer is seed(kn-a5b3d0ac-f6a1-49a4-aebb-b8b4cd67fe83) -> hub -> sibling, a two-hop traversal.",
+   "associative_source": "kn-a5b3d0ac-f6a1-49a4-aebb-b8b4cd67fe83",
+   "hub": "kn-5b606390-a52d-4ca2-8e0e-eba141d13440",
+   "siblings_dropped_for_overlap": 7
+  },
+  {
+   "id": "q31",
+   "category": "associative",
+   "query": "hope won inside the narrative preface",
+   "relevant": [
+    "kn-0bb4f021-56de-4947-a35b-a37209e7ba21",
+    "kn-22d77abe-b3c5-42fd-afcd-dcb87d924929",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40",
+    "kn-6061318f-046b-4935-907d-8eafdce14930",
+    "kn-78db5396-3dbc-4481-bfc7-e4e1422feb1c",
+    "kn-a5b3d0ac-f6a1-49a4-aebb-b8b4cd67fe83",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "kn-f230b362-b201-4402-9833-4160c89ab3d4"
+   ],
+   "derivation": "DERIVED FROM EDGES: the query is built from the distinctive vocabulary of kn-e0423482-cfa5-4796-8689-8495c93b66bc ('Value ? Hope Is a Conclusion'), which hangs off the values hub kn-5b606390-a52d-4ca2-8e0e-eba141d13440 by an `identity` edge. Expected answers are that node's SIBLINGS on the same hub (11 of 13; 2 dropped because they shared a query word and so were lexically reachable). Every remaining sibling shares ZERO content words with the query — the only route from query to answer is seed(kn-e0423482-cfa5-4796-8689-8495c93b66bc) -> hub -> sibling, a two-hop traversal.",
+   "associative_source": "kn-e0423482-cfa5-4796-8689-8495c93b66bc",
+   "hub": "kn-5b606390-a52d-4ca2-8e0e-eba141d13440",
+   "siblings_dropped_for_overlap": 2
+  },
+  {
+   "id": "q32",
+   "category": "associative",
+   "query": "man of the house six years old expectation",
+   "relevant": [
+    "015644f5-8194-4af0-800d-dd4a0cd71396",
+    "kn-0bb4f021-56de-4947-a35b-a37209e7ba21",
+    "kn-13f60407-7b70-4db1-964f-ea1f8196efbd",
+    "kn-22d77abe-b3c5-42fd-afcd-dcb87d924929",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40",
+    "kn-78db5396-3dbc-4481-bfc7-e4e1422feb1c",
+    "kn-a5b3d0ac-f6a1-49a4-aebb-b8b4cd67fe83",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "kn-e0423482-cfa5-4796-8689-8495c93b66bc"
+   ],
+   "derivation": "DERIVED FROM EDGES: the query is built from the distinctive vocabulary of kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8 ('Value ? Capability Is a Debt You Owe the Moment'), which hangs off the values hub kn-5b606390-a52d-4ca2-8e0e-eba141d13440 by an `identity` edge. Expected answers are that node's SIBLINGS on the same hub (11 of 13; 2 dropped because they shared a query word and so were lexically reachable). Every remaining sibling shares ZERO content words with the query — the only route from query to answer is seed(kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8) -> hub -> sibling, a two-hop traversal.",
+   "associative_source": "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+   "hub": "kn-5b606390-a52d-4ca2-8e0e-eba141d13440",
+   "siblings_dropped_for_overlap": 2
+  },
+  {
+   "id": "q33",
+   "category": "nonsense",
+   "query": "zqxjvw plimforth grebulon",
+   "relevant": [],
+   "derivation": "CONTROL: verified at build time that none of this string's tokens occurs anywhere in the corpus. Correct behaviour is to return NOTHING; any result is a false positive.",
+   "expect_empty": true
+  },
+  {
+   "id": "q34",
+   "category": "nonsense",
+   "query": "flarnbistle quommetry",
+   "relevant": [],
+   "derivation": "CONTROL: verified at build time that none of this string's tokens occurs anywhere in the corpus. Correct behaviour is to return NOTHING; any result is a false positive.",
+   "expect_empty": true
+  },
+  {
+   "id": "q35",
+   "category": "nonsense",
+   "query": "xxqzzt vurblenacht throom",
+   "relevant": [],
+   "derivation": "CONTROL: verified at build time that none of this string's tokens occurs anywhere in the corpus. Correct behaviour is to return NOTHING; any result is a false positive.",
+   "expect_empty": true
+  },
+  {
+   "id": "q36",
+   "category": "superseded",
+   "query": "is the self-improvement architecture called DARMA or DHARMA",
+   "relevant": [
+    "mem-80d7416b-20e9-48a0-b176-b215527e2f56"
+   ],
+   "derivation": "DERIVED: correction node is Will's confirmation that the H is intentional (DHARMA, not DARMA); the stale node is the surviving backlog item still titled 'Implement DARMA'. Scored on RANKING, not presence: the corrected node mem-80d7416b-20e9-48a0-b176-b215527e2f56 must be returned AND must rank above the stale node bl-5b17bd3b-0c41-46cb-a710-6fa4429692ff.",
+   "must_outrank": [
+    "mem-80d7416b-20e9-48a0-b176-b215527e2f56",
+    "bl-5b17bd3b-0c41-46cb-a710-6fa4429692ff"
+   ],
+   "stale_id": "bl-5b17bd3b-0c41-46cb-a710-6fa4429692ff",
+   "correct_label": "CORRECTION: The autonomous self-improvement architecture is DHARMA ? n",
+   "stale_label": "Implement DARMA ? Directed Autonomous Runtime Modification Architectur"
+  },
+  {
+   "id": "q37",
+   "category": "superseded",
+   "query": "how many provisional patents does Will actually have",
+   "relevant": [
+    "3cf706a1-3825-45d8-b0a9-06cae6cdf5b8"
+   ],
+   "derivation": "DERIVED: correction node is the 2026-06-17 confabulation flag establishing EXACTLY 6 provisionals; the stale node is the surviving memory that asserts 12 filed patents. Scored on RANKING, not presence: the corrected node 3cf706a1-3825-45d8-b0a9-06cae6cdf5b8 must be returned AND must rank above the stale node 936541a9-fabb-466b-9ca3-a78b17ad0c53.",
+   "must_outrank": [
+    "3cf706a1-3825-45d8-b0a9-06cae6cdf5b8",
+    "936541a9-fabb-466b-9ca3-a78b17ad0c53"
+   ],
+   "stale_id": "936541a9-fabb-466b-9ca3-a78b17ad0c53",
+   "correct_label": "memory:remembered",
+   "stale_label": "memory:remembered"
+  },
+  {
+   "id": "q38",
+   "category": "superseded",
+   "query": "is MCP still the live integration layer",
+   "relevant": [
+    "mem-30425134-6008-4fd9-a3ee-67a7742c319b"
+   ],
+   "derivation": "DERIVED: correction node is the 'CGI ARCHITECTURE - THREE LAYERS, MCP RETIRED' decision of April 30 2026; the stale node still records the MCP server as live. Scored on RANKING, not presence: the corrected node mem-30425134-6008-4fd9-a3ee-67a7742c319b must be returned AND must rank above the stale node mem-101e81b4-8097-4749-8d8d-7bb66de34517.",
+   "must_outrank": [
+    "mem-30425134-6008-4fd9-a3ee-67a7742c319b",
+    "mem-101e81b4-8097-4749-8d8d-7bb66de34517"
+   ],
+   "stale_id": "mem-101e81b4-8097-4749-8d8d-7bb66de34517",
+   "correct_label": "CGI ARCHITECTURE ? THREE LAYERS, MCP RETIRED (April 30, 2026). Definit",
+   "stale_label": "GCloud MCP infrastructure ? April 27, 2026. Legion died (~19:30 UTC). "
+  }
+ ]
+}

tools/retrieval-eval/legs.py

@@ -0,0 +1,117 @@
+import json,pickle,os,math,urllib.request,numpy as np
+S='/private/tmp/claude-501/-Users-timlingo/82369039-a20e-4b5a-8a5e-28234a57b996/scratchpad/sim/'
+C=pickle.load(open(S+'corpus.pkl','rb'))
+NODES=C['nodes']; EDGES=C['edges']; N=len(NODES)
+E=np.load(S+'emb.npy'); HAVE=np.load(S+'have.npy')
+En=E/np.maximum(np.linalg.norm(E,axis=1,keepdims=True),1e-12)
+LAYERS={int(l['layer_id']):l for l in (C['layers'] or [])} if C['layers'] else {}
+TRANS=set(i for i,l in LAYERS.items() if l.get('transparent'))
+def addressable(s):
+    if not s: return False
+    return all(0x20<=ord(ch)<=0x7e for ch in s)
+ADDR=np.array([addressable(n['id']) for n in NODES])
+OK=np.array([ (n['layer_id'] not in TRANS) and ADDR[i] for i,n in enumerate(NODES)])
+SAL=np.array([n['salience'] for n in NODES])
+LOW=[ (n['content']+'\x00'+n['label']+'\x00'+n['tags']).lower() for n in NODES]
+DL=np.array([float(len(n['content'])+len(n['label'])+len(n['tags'])) for n in NODES])
+IDX={}
+for i,n in enumerate(NODES):
+    IDX.setdefault(n['id'],i)
+STRUCT={"identity","contains","superseded_by","references","embodies","demonstrated_by","canonical-self","depends_on","currently_holds","activates"}
+ADJ_F=[[] for _ in range(N)]; ADJ_T=[[] for _ in range(N)]
+for e in EDGES:
+    a=IDX.get(e['from']); b=IDX.get(e['to'])
+    if a is None or b is None: continue
+    ADJ_F[a].append((e,b)); ADJ_T[b].append((e,a))
+EXCL=np.array([n['node_type'] in ('Tag','InternalStateEvent') for n in NODES])
+avgdl_all=None
+def tokenize(q):
+    out=[]
+    for t in q.split():
+        if not any(t.lower()==x.lower() for x in out): out.append(t)
+    return out
+_qcache={}
+def qemb(q):
+    if q in _qcache: return _qcache[q]
+    body=json.dumps({"model":"nomic-embed-text","prompt":q}).encode()
+    r=urllib.request.urlopen(urllib.request.Request("http://127.0.0.1:11434/api/embeddings",data=body,headers={"Content-Type":"application/json"}),timeout=30)
+    v=np.array(json.loads(r.read())["embedding"],dtype=np.float32)
+    v=v/np.linalg.norm(v); _qcache[q]=v; return v
+K1,B=1.2,0.75
+SEED_MIN=0.60; SEED_K=8; ASSOC_SEEDS=3; DEPTH=2; FIRE=0.02; AMAX=64; DECAY=0.7
+def legs(query):
+    toks=tokenize(query)
+    masks=[]; 
+    hit_idx=[]; hit_mask=[]
+    df=[0]*len(toks)
+    lt=[t.lower() for t in toks]
+    for i in range(N):
+        if not OK[i]: continue
+        s=LOW[i]; m=0
+        for t,tok in enumerate(lt):
+            if tok in s: m|=(1<<t)
+        if m:
+            hit_idx.append(i); hit_mask.append(m)
+            for t in range(len(toks)):
+                if m>>t&1: df[t]+=1
+    dl_n=int(OK.sum()); avgdl=float(DL[OK].sum()/max(dl_n,1))
+    idf=[math.log(1.0+((dl_n-d+0.5)/(d+0.5))) for d in df]
+    L=[]
+    for j,i in enumerate(hit_idx):
+        norm=1.0-B+B*(DL[i]/avgdl); w=0.0
+        for t in range(len(toks)):
+            if hit_mask[j]>>t&1: w+=idf[t]*(K1+1.0)/(1.0+K1*norm)
+        L.append((i,w,SAL[i]))
+    L.sort(key=lambda x:(-x[1],-x[2]))
+    qv=qemb(query)
+    cos=En@qv
+    cos=np.where(HAVE&OK,cos,-2.0)
+    order=np.argsort(-cos)
+    semfull=[(int(i),float(cos[i])) for i in order[:400]]
+    Sleg=[(i,(c-SEED_MIN)/(1-SEED_MIN)) for i,c in semfull if c>SEED_MIN]
+    semseed=[i for i,c in semfull[:SEED_K] if c>0.0]
+    # assoc
+    act={}; seen={}; qq=[]
+    for i,_,_ in L[:ASSOC_SEEDS]:
+        act[i]=1.0; seen[i]=2; qq.append((i,0))
+    for i in semseed:
+        if i in seen: continue
+        act[i]=1.0; seen[i]=2; qq.append((i,0))
+    qh=0
+    while qh<len(qq):
+        cur,h=qq[qh]; qh+=1
+        if h>=DEPTH: continue
+        parent=act[cur]
+        for e,oi in ADJ_F[cur]+ADJ_T[cur]:
+            if e['rel'] not in STRUCT: continue
+            if EXCL[oi]: continue
+            na=parent*e['w']*DECAY*SAL[oi]
+            if na<FIRE: continue
+            if seen.get(oi) and na<=act.get(oi,0): continue
+            act[oi]=na
+            if not seen.get(oi): seen[oi]=1
+            if len(qq)<AMAX*4: qq.append((oi,h+1))
+    A=[]
+    for i,st in seen.items():
+        if st!=1: continue
+        if not OK[i] or not HAVE[i]: continue
+        c=float(cos[i])
+        if c<=0.0: continue
+        A.append((i,c))
+    A.sort(key=lambda x:-x[1]); A=A[:AMAX]
+    return L,Sleg,A,cos
+def interleave3(L,Sl,A,lim=10):
+    out=[]; li=si=ai=0
+    while len(out)<lim and (li<len(L) or si<len(Sl) or ai<len(A)):
+        if li<len(L):
+            if L[li][0] not in out: out.append(L[li][0])
+            li+=1
+        if len(out)>=lim: break
+        if si<len(Sl):
+            if Sl[si][0] not in out: out.append(Sl[si][0])
+            si+=1
+        if len(out)>=lim: break
+        if ai<len(A):
+            if A[ai][0] not in out: out.append(A[ai][0])
+            ai+=1
+    return out

tools/retrieval-eval/merge-corpus.py

@@ -0,0 +1,17 @@
+import json,sys
+SRC="/Users/timlingo/neuron-memory-backups/snapshot-pre-repair-20260806.json"
+TSV,OUT=sys.argv[1],sys.argv[2]
+emb={}
+for line in open(TSV,encoding='utf-8',errors='surrogateescape'):
+    p=line.rstrip("\n").rsplit("\t",1)
+    if len(p)==2 and p[1].count(",")>100: emb[p[0]]=p[1]
+print("vectors",len(emb),flush=True)
+d=json.load(open(SRC,encoding='utf-8',errors='surrogateescape'))
+hit=0
+for n in d["nodes"]:
+    v=emb.get(n.get("id") or "")
+    if v: n["emb"]=v; hit+=1
+print("attached",hit,"of",len(d["nodes"]),flush=True)
+with open(OUT,"w",encoding='utf-8',errors='surrogateescape') as f:
+    json.dump(d,f,ensure_ascii=False)
+print("wrote",OUT,flush=True)

tools/retrieval-eval/policy2.py

@@ -0,0 +1,102 @@
+import json,sys,pickle,numpy as np
+sys.path.insert(0,'.')
+from legs import *
+GP='/Users/timlingo/Development/neuron-technologies/_wt-bm25lex/tools/retrieval-eval/'
+G=json.load(open(GP+'gold_set.json'))
+def legs3(query, sem_sal=False, assoc_sal=False, unfloor=False, sem_cap=None):
+    toks=tokenize(query)
+    hit_idx=[];hit_mask=[];df=[0]*len(toks);lt=[t.lower() for t in toks]
+    for i in range(N):
+        if not OK[i]: continue
+        s=LOW[i];m=0
+        for t,tok in enumerate(lt):
+            if tok in s: m|=(1<<t)
+        if m:
+            hit_idx.append(i);hit_mask.append(m)
+            for t in range(len(toks)):
+                if m>>t&1: df[t]+=1
+    dl_n=int(OK.sum());avgdl=float(DL[OK].sum()/max(dl_n,1))
+    idf=[math.log(1.0+((dl_n-d+0.5)/(d+0.5))) for d in df]
+    L=[]
+    for j,i in enumerate(hit_idx):
+        norm=1.0-B+B*(DL[i]/avgdl);w=0.0
+        for t in range(len(toks)):
+            if hit_mask[j]>>t&1: w+=idf[t]*(K1+1.0)/(1.0+K1*norm)
+        L.append((i,w,SAL[i]))
+    L.sort(key=lambda x:(-x[1],-x[2]))
+    if not L: return [],[],[]
+    qv=qemb(query);cos=En@qv;cos=np.where(HAVE&OK,cos,-2.0)
+    order=np.argsort(-cos)[:600]
+    cand=[int(i) for i in order if cos[i]>(0.0 if unfloor else SEED_MIN)]
+    key=(lambda i:(SAL[i] if sem_sal else 1.0)*float(cos[i]))
+    Sl=sorted(cand,key=lambda i:-key(i))
+    if sem_cap: Sl=Sl[:sem_cap]
+    semseed=[int(i) for i in order[:SEED_K] if cos[i]>0.0]
+    act={};seen={};qq=[]
+    for i,_,_ in L[:ASSOC_SEEDS]:
+        act[i]=1.0;seen[i]=2;qq.append((i,0))
+    for i in semseed:
+        if i in seen: continue
+        act[i]=1.0;seen[i]=2;qq.append((i,0))
+    qh=0
+    while qh<len(qq):
+        cur,h=qq[qh];qh+=1
+        if h>=DEPTH: continue
+        parent=act[cur]
+        for e,oi in ADJ_F[cur]+ADJ_T[cur]:
+            if e['rel'] not in STRUCT: continue
+            if EXCL[oi]: continue
+            na=parent*e['w']*DECAY*SAL[oi]
+            if na<FIRE: continue
+            if seen.get(oi) and na<=act.get(oi,0): continue
+            act[oi]=na
+            if not seen.get(oi): seen[oi]=1
+            if len(qq)<AMAX*4: qq.append((oi,h+1))
+    A=[]
+    for i,st in seen.items():
+        if st!=1 or not OK[i] or not HAVE[i]: continue
+        c=float(cos[i])
+        if c<=0.0: continue
+        A.append((i,(SAL[i] if assoc_sal else 1.0)*c))
+    A.sort(key=lambda x:-x[1]);A=[i for i,_ in A[:AMAX]]
+    return [i for i,_,_ in L],Sl,A
+def merge(L,S,A,lim=10):
+    out=[];li=si=ai=0
+    while len(out)<lim and (li<len(L) or si<len(S) or ai<len(A)):
+        if li<len(L):
+            if L[li] not in out: out.append(L[li])
+            li+=1
+        if len(out)>=lim: break
+        if si<len(S):
+            if S[si] not in out: out.append(S[si])
+            si+=1
+        if len(out)>=lim: break
+        if ai<len(A):
+            if A[ai] not in out: out.append(A[ai])
+            ai+=1
+    return out
+def outcome(q,ids):
+    c=q['category']
+    if c=='nonsense': return len(ids)==0
+    if c=='superseded':
+        a,b=q['must_outrank']
+        if a not in ids: return False
+        if b not in ids: return True
+        return ids.index(a)<ids.index(b)
+    return any(x in ids[:5] for x in q['relevant'])
+def run(**kw):
+    return {q['id']:outcome(q,[NODES[i]['id'] for i in merge(*legs3(q['query'],**kw),10)]) for q in G['queries']}
+base=run()
+print("baseline",sum(base.values()),"/38  misses:",[k for k,v in base.items() if not v])
+import itertools
+for name,kw in [
+  ('sem_sal(floored)',dict(sem_sal=True)),
+  ('unfloor',dict(unfloor=True)),
+  ('unfloor+sem_sal',dict(unfloor=True,sem_sal=True)),
+  ('assoc_sal',dict(assoc_sal=True)),
+  ('unfloor+sem_sal+assoc_sal',dict(unfloor=True,sem_sal=True,assoc_sal=True)),
+  ('sem_sal+assoc_sal(floored)',dict(sem_sal=True,assoc_sal=True)),
+]:
+    r=run(**kw)
+    g=sorted(k for k in base if r[k] and not base[k]); l=sorted(k for k in base if base[k] and not r[k])
+    print("%-28s net=%+d gains=%s losses=%s"%(name,len(g)-len(l),g,l))

tools/retrieval-eval/results-act-r2.json

@@ -0,0 +1,942 @@
+{
+ "label": "act-r2",
+ "soul_binary": "/private/tmp/claude-501/-Users-timlingo/82369039-a20e-4b5a-8a5e-28234a57b996/scratchpad/soul-act",
+ "soul_md5": "77722f5a9f49494bf735c2a4be1b5dc4",
+ "corpus": "/Users/timlingo/neuron-memory-backups/snapshot-pre-repair-20260806.json",
+ "corpus_nodes": 78768,
+ "corpus_edges": 14214,
+ "gold_set": "/Users/timlingo/Development/neuron-technologies/_wt-eval/tools/retrieval-eval/gold_set.json",
+ "limit": 10,
+ "port": 7902,
+ "wall_clock_s": 121.2,
+ "child_pid": 78714,
+ "child_confirmed_dead": true,
+ "aggregate": {
+  "n_queries": 38,
+  "n_scored": 35,
+  "hit@5": 0.22857142857142856,
+  "recall@5": 0.18908730158730158,
+  "recall@10": 0.24277210884353742,
+  "precision@5": 0.06857142857142857,
+  "mrr@10": 0.24154195011337865,
+  "nonsense_clean": "2/3",
+  "superseded_outranks": "0/3",
+  "latency_ms_p50": 3237.6,
+  "latency_ms_p95": 5264.0,
+  "latency_ms_max": 5510.9,
+  "errors": 0,
+  "by_category": {
+   "associative": {
+    "n": 6,
+    "hit@5": 0.0,
+    "recall@5": 0.0,
+    "recall@10": 0.0,
+    "mrr@10": 0.0
+   },
+   "exact_rare": {
+    "n": 6,
+    "hit@5": 1.0,
+    "recall@5": 1.0,
+    "recall@10": 1.0,
+    "mrr@10": 1.0
+   },
+   "nonsense": {
+    "n": 3,
+    "clean": 2,
+    "avg_false_positives": 2.6666666666666665
+   },
+   "paraphrase": {
+    "n": 13,
+    "hit@5": 0.0,
+    "recall@5": 0.0,
+    "recall@10": 0.0,
+    "mrr@10": 0.0
+   },
+   "phrase": {
+    "n": 7,
+    "hit@5": 0.2857142857142857,
+    "recall@5": 0.0882936507936508,
+    "recall@10": 0.3567176870748299,
+    "mrr@10": 0.3505668934240363
+   },
+   "superseded": {
+    "n": 3,
+    "hit@5": 0.0,
+    "recall@5": 0.0,
+    "recall@10": 0.0,
+    "mrr@10": 0.0,
+    "outranks": 0
+   }
+  }
+ },
+ "rows": [
+  {
+   "id": "q01",
+   "category": "exact_rare",
+   "query": "unjailbreakable",
+   "returned": [
+    "mem-7f61beb4-271c-4feb-9f6e-1c9c837a6226"
+   ],
+   "n_returned": 1,
+   "latency_ms": 476.5,
+   "error": null,
+   "hit@5": 1.0,
+   "recall@5": 1.0,
+   "recall@10": 1.0,
+   "precision@5": 0.2,
+   "mrr@10": 1.0
+  },
+  {
+   "id": "q02",
+   "category": "exact_rare",
+   "query": "engram-migrate",
+   "returned": [
+    "mem-6fdf6545-5e1a-43a9-8bdc-d2cd248146a5"
+   ],
+   "n_returned": 1,
+   "latency_ms": 708.1,
+   "error": null,
+   "hit@5": 1.0,
+   "recall@5": 1.0,
+   "recall@10": 1.0,
+   "precision@5": 0.2,
+   "mrr@10": 1.0
+  },
+  {
+   "id": "q03",
+   "category": "exact_rare",
+   "query": "cartabandonedevent",
+   "returned": [
+    "mem-1ba7c67d-85b9-4c2e-9fe2-39f8b0477091"
+   ],
+   "n_returned": 1,
+   "latency_ms": 532.0,
+   "error": null,
+   "hit@5": 1.0,
+   "recall@5": 1.0,
+   "recall@10": 1.0,
+   "precision@5": 0.2,
+   "mrr@10": 1.0
+  },
+  {
+   "id": "q04",
+   "category": "exact_rare",
+   "query": "pre-apprenticeship",
+   "returned": [
+    "mem-89c02aae-d3ca-43f9-9e5d-eb369896276c"
+   ],
+   "n_returned": 1,
+   "latency_ms": 537.5,
+   "error": null,
+   "hit@5": 1.0,
+   "recall@5": 1.0,
+   "recall@10": 1.0,
+   "precision@5": 0.2,
+   "mrr@10": 1.0
+  },
+  {
+   "id": "q05",
+   "category": "exact_rare",
+   "query": "inferencenodemanager",
+   "returned": [
+    "mem-73969486-143f-4431-b5e6-6845d1cc9848"
+   ],
+   "n_returned": 1,
+   "latency_ms": 568.7,
+   "error": null,
+   "hit@5": 1.0,
+   "recall@5": 1.0,
+   "recall@10": 1.0,
+   "precision@5": 0.2,
+   "mrr@10": 1.0
+  },
+  {
+   "id": "q06",
+   "category": "exact_rare",
+   "query": "clear-eyed",
+   "returned": [
+    "knw-c72597c5-c23d-4c08-8e9e-996dadf26a99"
+   ],
+   "n_returned": 1,
+   "latency_ms": 555.4,
+   "error": null,
+   "hit@5": 1.0,
+   "recall@5": 1.0,
+   "recall@10": 1.0,
+   "precision@5": 0.2,
+   "mrr@10": 1.0
+  },
+  {
+   "id": "q07",
+   "category": "phrase",
+   "query": "patterns not returns",
+   "returned": [
+    "knw-d357b6bb-ad8a-4791-b516-426aea45fa5b",
+    "kn-69fd6e83-7718-4824-8d66-f49d8954e224",
+    "kn-d97920d0-1649-4223-9508-c0bb621e7fc0",
+    "kn-57b4c5e7-40c6-4c90-bf14-71841b0081d4",
+    "kn-c3d9d063-8c5d-45aa-900c-550914b2ff6d",
+    "kn-f838f113-76d5-4a15-9cef-14055c4723a3",
+    "bl-76e878aa-e1fe-468c-bf9c-854097cb7e0b",
+    "art-c71aef51-026f-4d63-80e9-2a0ec0dc3865",
+    "bl-e148d23c-24e8-4122-9915-d1c11f22052f",
+    "bl-31abf75b-998f-4a4f-a6dd-8204119e0451"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1906.2,
+   "error": null,
+   "hit@5": 0.0,
+   "recall@5": 0.0,
+   "recall@10": 0.0,
+   "precision@5": 0.0,
+   "mrr@10": 0.0
+  },
+  {
+   "id": "q08",
+   "category": "phrase",
+   "query": "thirty moves",
+   "returned": [
+    "knw-7902acca-604e-409b-8faf-ad85424211d0",
+    "bl-80720fdf-7ce7-4d28-aff8-21028d3a8cfb",
+    "art-2f29ad36-6ee6-4a0e-8d72-0eaf7d12d3a9",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "knw-ed33e669-0790-44cb-a036-958d605c6fea",
+    "kn-6061318f-046b-4935-907d-8eafdce14930",
+    "art-80ca3d31-84dc-4502-83f4-538372b9764f",
+    "knw-2c46cfb4-6d4e-4822-8a1a-7d743c1e4329",
+    "?Z?.\f?0?]P?",
+    "?Q??m?;��`'"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1103.3,
+   "error": null,
+   "hit@5": 1.0,
+   "recall@5": 0.0625,
+   "recall@10": 0.1875,
+   "precision@5": 0.2,
+   "mrr@10": 1.0
+  },
+  {
+   "id": "q09",
+   "category": "phrase",
+   "query": "Grandma Lucas",
+   "returned": [
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "? ?}&?#??X\b",
+    "art-0f0277a1-4a8e-4645-95dd-fa379976f31c",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "766de879-f9d0-4a07-b6df-b43ee13763d8",
+    "art-79042b8b-6192-440f-90b0-60708f7e6325"
+   ],
+   "n_returned": 6,
+   "latency_ms": 1132.4,
+   "error": null,
+   "hit@5": 1.0,
+   "recall@5": 0.5555555555555556,
+   "recall@10": 0.5555555555555556,
+   "precision@5": 1.0,
+   "mrr@10": 1.0
+  },
+  {
+   "id": "q10",
+   "category": "phrase",
+   "query": "Directed Harmonic",
+   "returned": [
+    "bl-c9adb8e5-293f-4033-99f8-0405c17ef941",
+    "bl-7e7c3fdb-4132-487f-aa70-b2cd559cb7f0",
+    "bl-7aebe936-ac55-4f35-8932-adc5224ff854",
+    "bl-9d53422d-b703-4f1d-860a-8598cb29b792",
+    "mem-34f53a9d-a131-4f82-9dbd-b9eb4a9af52e",
+    "mem-60778715-758c-4677-933d-fc39b8f94152",
+    "? ?}&?#??X\b",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "knw-e24d6339-5ff3-4bed-ba53-707ffd0dc70a",
+    "mem-7eeacad7-d7c2-4c2b-8348-19a59aa6dbaf"
+   ],
+   "n_returned": 10,
+   "latency_ms": 960.8,
+   "error": null,
+   "hit@5": 0.0,
+   "recall@5": 0.0,
+   "recall@10": 0.1111111111111111,
+   "precision@5": 0.0,
+   "mrr@10": 0.1
+  },
+  {
+   "id": "q11",
+   "category": "phrase",
+   "query": "Sarah Bishop",
+   "returned": [
+    "art-ddfcd045-2c3b-4a1e-9966-fec5ce44e1dd",
+    "art-4a99aa1a-489b-4b43-958b-25217adb1aad",
+    ";??A5???",
+    "art-94fae615-7cd5-4695-b968-977101b06a51",
+    "art-2fabd873-d787-49cb-ad30-d4ed9fcff8ef",
+    "mem-a9a9ce95-0d64-46eb-9db8-ff81d78ade35",
+    "mem-57164d5f-baf0-4149-957a-379a4e255d1a",
+    "? ?}&?#??X\b",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "art-8dbceb06-431a-416d-a723-e8c75d595154"
+   ],
+   "n_returned": 10,
+   "latency_ms": 992.4,
+   "error": null,
+   "hit@5": 0.0,
+   "recall@5": 0.0,
+   "recall@10": 0.5,
+   "precision@5": 0.0,
+   "mrr@10": 0.1111111111111111
+  },
+  {
+   "id": "q12",
+   "category": "phrase",
+   "query": "Directed Autonomous Runtime Modification",
+   "returned": [
+    "kn-b2a99cd7-b379-4d9b-a996-e347a02c7bad",
+    "bl-a313d67b-dd6d-4e5b-a55a-03bc7bda17ae",
+    "kn-8e1bfb48-33a9-45ad-8da7-e0bdaa5d34e7",
+    "art-92e1837c-5919-42d0-bbb0-4d924d7b2864",
+    "bl-a7a1428f-db9c-417b-8e2c-713b1f84dc1f",
+    "mem-f823e835-313f-4282-b4b3-ce527ffc2f7a",
+    "? ?}&?#??X\b",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "?Z?.\f?0?]P?",
+    "bl-145a0985-2382-400f-a7c5-c335c5e30a72"
+   ],
+   "n_returned": 10,
+   "latency_ms": 2820.6,
+   "error": null,
+   "hit@5": 0.0,
+   "recall@5": 0.0,
+   "recall@10": 0.14285714285714285,
+   "precision@5": 0.0,
+   "mrr@10": 0.14285714285714285
+  },
+  {
+   "id": "q13",
+   "category": "phrase",
+   "query": "zero-knowledge encrypted backup",
+   "returned": [
+    "art-e495c8c5-ad95-4b64-8771-f68aa4cfcd0a",
+    "kn-5584ef9c-7f9d-4d7c-a10a-4ee6bc5cf356",
+    "bl-e20944e5-eb16-4ab3-a84d-111e0fc817fa",
+    "bl-e20944e5-f4a6-44a0-91b1-73d04ebed120",
+    "mem-47f72b5b-6e8b-4293-94f1-350197b4809a",
+    "mem-a5f04e52-91f8-41d2-af27-8bf803621758",
+    "7774a16c-1027-4e3b-a21e-67f1f95a4acd",
+    "? ?}&?#??X\b",
+    "7?e?7???\f3?",
+    "deda48cd-5e1a-46cb-bd43-8016afdb3a8a"
+   ],
+   "n_returned": 10,
+   "latency_ms": 2609.4,
+   "error": null,
+   "hit@5": 0.0,
+   "recall@5": 0.0,
+   "recall@10": 1.0,
+   "precision@5": 0.0,
+   "mrr@10": 0.1
+  },
+  {
+   "id": "q14",
+   "category": "paraphrase",
+   "query": "the elderly relative who passed while he stayed away",
+   "returned": [
+    "knw-6b48dce2-f21c-452a-9db5-4e6aa61c87ca",
+    "kn-82be4e41-96c5-4da3-85c0-cee10763d975",
+    "mem-ea487cb4-ed67-44ce-8402-b56bb28468d4",
+    "bl-2694b588-a6e3-43de-861c-fa7b0ec7e7fd",
+    "bl-14883d81-f7cb-46dd-82c2-a6e6980264e5",
+    "tag-dark-theme",
+    "art-0f0277a1-4a8e-4645-95dd-fa379976f31c",
+    "? ?}&?#??X\b",
+    "art-ddfcd045-2c3b-4a1e-9966-fec5ce44e1dd",
+    "art-4a99aa1a-489b-4b43-958b-25217adb1aad"
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+   "recall@5": 0.0,
+   "recall@10": 0.0,
+   "precision@5": 0.0,
+   "mrr@10": 0.0
+  },
+  {
+   "id": "q15",
+   "category": "paraphrase",
+   "query": "a soldier sidelined by illness who refused to quit",
+   "returned": [
+    "mem-0328c3cb-4550-4ce4-9284-152e832f08f6",
+    "bl-07375bf9-a169-42cd-adb3-7d32b25982f0",
+    "kn-57b4c5e7-40c6-4c90-bf14-71841b0081d4",
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+    "art-2f29ad36-6ee6-4a0e-8d72-0eaf7d12d3a9",
+    "art-0f0277a1-4a8e-4645-95dd-fa379976f31c",
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+    ";??A5???"
+   ],
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+  },
+  {
+   "id": "q16",
+   "category": "paraphrase",
+   "query": "choosing an uncomfortable fact over a pleasant fiction",
+   "returned": [
+    "bl-d24fcce8-2b55-426f-867a-db3958a622d3",
+    "tag-phase-3",
+    "tag-project-structure",
+    "tag-anthropic-contrast",
+    "tag-voice-training",
+    "tag-ebd",
+    "art-80ca3d31-84dc-4502-83f4-538372b9764f",
+    "bl-9d53422d-b703-4f1d-860a-8598cb29b792",
+    ";??A5???",
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q17",
+   "category": "paraphrase",
+   "query": "a tight payload beats a bloated one",
+   "returned": [
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+    "bl-57c5cf6b-81a5-4558-9902-5c02981fe273",
+    "tag-guilds",
+    "tag-kids",
+    "tag-coexistence",
+    "tag-cultivated-general-intelligence",
+    "? ?}&?#??X\b",
+    "kn-d7c1e0fb-fa59-46d3-b4c9-a0d1d437a491",
+    ";??A5???",
+    "mem-cdff0c49-3ac7-4de8-89ec-92d254bd0023"
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+  },
+  {
+   "id": "q18",
+   "category": "paraphrase",
+   "query": "if you are able and nobody is coming the job is yours",
+   "returned": [
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+    "bl-bd9fb314-e9d4-4b03-aef4-534dd57a2992",
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+    "bl-e98cdd4c-01b5-459e-9036-3578cd5d975a",
+    "bl-9ce4128a-9436-4b06-82bc-8a6faafa81e0",
+    "tag-stable-diffusion",
+    ";??A5???",
+    "art-0f0277a1-4a8e-4645-95dd-fa379976f31c",
+    "art-80ca3d31-84dc-4502-83f4-538372b9764f",
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q19",
+   "category": "paraphrase",
+   "query": "learning is the wealth creditors cannot seize",
+   "returned": [
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+    "mem-e32ba5a7-c147-4dc0-9479-b720d768eda6",
+    "mem-c7a77457-478d-4eb0-a116-67205a0066a4",
+    "bl-1b20e9bc-eb37-4907-8d63-e311fd61eab8",
+    "bl-aa762207-920d-45ab-b2a3-2f8154d7ef9b",
+    "tag-misalignment",
+    "art-0f0277a1-4a8e-4645-95dd-fa379976f31c",
+    "? ?}&?#??X\b",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q20",
+   "category": "paraphrase",
+   "query": "reliability proven by track record not assertion",
+   "returned": [
+    "kn-48a01973-a025-471d-950f-b93e6a426d82",
+    "mem-23d22bc1-a097-446b-8f11-8aff099e0b76",
+    "mem-6f0b2b45-90c1-4356-ac01-3daac05b09c8",
+    "mem-ce5a2ffc-ad39-4728-9ac6-76fef507d5da",
+    "project-Stripe_Elements__not_hosted_checkout__Custom_URL__DAG_bundle_pricing__Stripe_Connect_80_20_",
+    "tag-provenance",
+    "? ?}&?#??X\b",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "art-2f29ad36-6ee6-4a0e-8d72-0eaf7d12d3a9",
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+  },
+  {
+   "id": "q21",
+   "category": "paraphrase",
+   "query": "boundaries that enable instead of confine",
+   "returned": [
+    "kn-79056192-7de8-486c-9565-f128439a6fcb",
+    "bl-f6236350-f7b8-4f4f-a702-9eef2eb76e4b",
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+    "mem-1f32f73a-952c-41bc-96dc-8b8b70d8a7c1",
+    "tag-__cultivation-metric____internal-state____dharma____evidence____novel-idea____gap-compression____values____microsoft__",
+    "? ?}&?#??X\b",
+    "kn-d7c1e0fb-fa59-46d3-b4c9-a0d1d437a491",
+    "art-80ca3d31-84dc-4502-83f4-538372b9764f",
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+  },
+  {
+   "id": "q22",
+   "category": "paraphrase",
+   "query": "what shifts tells you where to cut a system apart",
+   "returned": [
+    "knw-723551f5-1950-42a3-8b89-b6a06913cef0",
+    "tag-identity-studio",
+    "tag-finance",
+    "tag-temporal",
+    "tag-barkhausen",
+    "tag-ilogger",
+    "tag-design-first",
+    ";??A5???",
+    "art-0f0277a1-4a8e-4645-95dd-fa379976f31c",
+    "? ?}&?#??X\b"
+   ],
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q23",
+   "category": "paraphrase",
+   "query": "a mind that compounds instead of resetting each day",
+   "returned": [
+    "project-Goal_setting__alignment__scoring__cadence__Attaches_to_any_imprint_",
+    "tag-performed-values",
+    "tag-turing-test",
+    "tag-sealed",
+    "tag-part-5",
+    "tag-model",
+    "art-80ca3d31-84dc-4502-83f4-538372b9764f",
+    "art-ddfcd045-2c3b-4a1e-9966-fec5ce44e1dd",
+    "? ?}&?#??X\b",
+    ";??A5???"
+   ],
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+  },
+  {
+   "id": "q24",
+   "category": "paraphrase",
+   "query": "loved for the unedited self and not the polished exterior",
+   "returned": [
+    "mem-9590ba23-bddb-43e8-a571-68a263c4c364",
+    "project-Imprint__leadership_development__feedback_frameworks__performance__presence_",
+    "bl-a9e57bb2-00a1-4867-ab59-5d9271134b50",
+    "bl-c7793c4a-7630-47fc-a462-d23059087e80",
+    "tag-gateway_platform_neuron-technologies_go_proxy_llm",
+    "tag-fornax",
+    ";??A5???",
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q25",
+   "category": "paraphrase",
+   "query": "cheerfulness you arrive at instead of assuming",
+   "returned": [
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+    "bl-3f57bc69-7285-4f4a-a861-2de52efca058",
+    "bl-5e390b10-8753-4f25-a1a5-b5dbbb002cbf",
+    "tag-ats",
+    "tag-data-model",
+    "tag-aggregation",
+    "art-0f0277a1-4a8e-4645-95dd-fa379976f31c",
+    "art-80ca3d31-84dc-4502-83f4-538372b9764f",
+    ";??A5???",
+    "? ?}&?#??X\b"
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+  },
+  {
+   "id": "q26",
+   "category": "paraphrase",
+   "query": "a childhood offering no solid foundation to inherit",
+   "returned": [
+    "tag-memory-model",
+    "tag-storage",
+    "tag-ga4",
+    "tag-potions",
+    "tag-resonance",
+    "tag-neuron",
+    "? ?}&?#??X\b",
+    ";??A5???",
+    "art-0f0277a1-4a8e-4645-95dd-fa379976f31c",
+    "art-ddfcd045-2c3b-4a1e-9966-fec5ce44e1dd"
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q27",
+   "category": "associative",
+   "query": "Grandma Lucas stroke February 2006 goodbye window",
+   "returned": [
+    "mem-927f41ab-8ede-4f58-acb3-995db16ac775",
+    "mem-dbe80bc2-c602-46b0-b4ea-dd222e52bcde",
+    "mem-82158b02-a180-435d-84f0-0b7ce37511b4",
+    "bl-33ecccc2-e37f-43db-91b3-c2a86f08aaac",
+    "bl-4476e856-c567-4b49-8ff7-d7dca3e5715e",
+    "tag-upload-window",
+    "? ?}&?#??X\b",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "art-79042b8b-6192-440f-90b0-60708f7e6325"
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q28",
+   "category": "associative",
+   "query": "Marines hernia sepsis medical ward",
+   "returned": [
+    "knw-920c891f-bb8c-48c4-9afc-018ef12dcdc4",
+    "knw-08559f5c-2306-4220-a146-398c74f1643c",
+    "mem-434be7c8-88cb-4039-b79a-1da4ac4de783",
+    "mem-481c769c-68cc-45c7-bc37-c0d9778fa648",
+    "bl-5b17bd3b-0c41-46cb-a710-6fa4429692ff",
+    "bl-9d8f3c5b-4bac-41ce-8ac4-44733f99d6c8",
+    "bl-33ecccc2-e37f-43db-91b3-c2a86f08aaac",
+    "art-ddfcd045-2c3b-4a1e-9966-fec5ce44e1dd",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "art-79042b8b-6192-440f-90b0-60708f7e6325"
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q29",
+   "category": "associative",
+   "query": "Sarah Bishop Dyer trailer performance",
+   "returned": [
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "kn-f8974b26-78a6-4aad-b893-19a73b20013d",
+    "kn-eb1c6d99-d603-4f33-be9a-c63a178690c6",
+    "mem-a3124d5b-2f50-477f-8bb5-06879f5a496c",
+    "bl-7fa1b1a8-b80a-4f28-b162-bfe73765b4f8",
+    "mem-89c02aae-d3ca-43f9-9e5d-eb369896276c",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "? ?}&?#??X\b",
+    "art-4a99aa1a-489b-4b43-958b-25217adb1aad",
+    "art-ddfcd045-2c3b-4a1e-9966-fec5ce44e1dd"
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q30",
+   "category": "associative",
+   "query": "Swarm Architecture containment lateral worker",
+   "returned": [
+    "mem-265a7107-73b3-4410-9aff-43787d5f473b",
+    "mem-9d1bf963-1b40-4588-bdb3-0432646cc623",
+    "mem-46780047-63a0-4a86-a16b-638b72a7fb8d",
+    "mem-3987d374-3c48-4e8e-b06d-0c363f55ed9c",
+    "bl-e0a0df72-de6e-46ab-800b-e1e3e8dfc387",
+    "tag-__patents____swarm____claim-language____prior-art____filing__",
+    "? ?}&?#??X\b",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "7?e?7???\f3?",
+    "?of?7???"
+   ],
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+   "error": null,
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+   "recall@5": 0.0,
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+   "precision@5": 0.0,
+   "mrr@10": 0.0
+  },
+  {
+   "id": "q31",
+   "category": "associative",
+   "query": "hope won inside the narrative preface",
+   "returned": [
+    "kn-dca14c4c-4859-47b0-996e-33964ba61a87",
+    "bl-dc8c7e02-eb37-48ae-a6f8-9b512803ae16",
+    "mem-8d1bafe6-209c-456c-9a25-9a927bc5a16d",
+    "bl-0de4e61b-6562-49e5-b7df-ebb809a01723",
+    "bl-8ef1ba6b-3fa0-4dbd-98c5-31665e5694a1",
+    "mem-22f5f665-3ad2-4063-88b0-915849a795f5",
+    "? ?}&?#??X\b",
+    "art-ddfcd045-2c3b-4a1e-9966-fec5ce44e1dd",
+    "?Q??m?;��`'",
+    "R^??m?;��?'"
+   ],
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+   "error": null,
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q32",
+   "category": "associative",
+   "query": "man of the house six years old expectation",
+   "returned": [
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "mem-394cc9e8-049b-45bc-a380-66314f14e367",
+    "bl-ffa22d7e-42a9-4bd2-a428-1d2df243ac93",
+    "bl-4a6746e8-191f-48fc-8bfb-c4dc73b80bcd",
+    "tag-command-pattern",
+    "tag-withholding",
+    "tag-offline",
+    "art-80ca3d31-84dc-4502-83f4-538372b9764f",
+    "art-0f0277a1-4a8e-4645-95dd-fa379976f31c",
+    "? ?}&?#??X\b"
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+  },
+  {
+   "id": "q33",
+   "category": "nonsense",
+   "query": "zqxjvw plimforth grebulon",
+   "returned": [],
+   "n_returned": 0,
+   "latency_ms": 1333.9,
+   "error": null,
+   "clean": true,
+   "false_positives": 0
+  },
+  {
+   "id": "q34",
+   "category": "nonsense",
+   "query": "flarnbistle quommetry",
+   "returned": [],
+   "n_returned": 0,
+   "latency_ms": 880.7,
+   "error": null,
+   "clean": true,
+   "false_positives": 0
+  },
+  {
+   "id": "q35",
+   "category": "nonsense",
+   "query": "xxqzzt vurblenacht throom",
+   "returned": [
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+    "? ?}&?#??X\b",
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+    "project-worldweaver",
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+   "query": "how many provisional patents does Will actually have",
+   "returned": [
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+    "? ?}&?#??X\b",
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+    "bl-8116da7a-b039-4e08-b8d0-c1c7861f9766",
+    "tag-enterprise",
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+    "???Ͼd??W\b?",
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+}

tools/retrieval-eval/results-act-r3.json

@@ -0,0 +1,942 @@
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+    "tag-phase-3",
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+   "query": "a mind that compounds instead of resetting each day",
+   "returned": [
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+    "tag-performed-values",
+    "tag-turing-test",
+    "tag-sealed",
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+  },
+  {
+   "id": "q24",
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+   "query": "loved for the unedited self and not the polished exterior",
+   "returned": [
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+    "project-Imprint__leadership_development__feedback_frameworks__performance__presence_",
+    "bl-a9e57bb2-00a1-4867-ab59-5d9271134b50",
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+  {
+   "id": "q25",
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+   "query": "cheerfulness you arrive at instead of assuming",
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+  {
+   "id": "q26",
+   "category": "paraphrase",
+   "query": "a childhood offering no solid foundation to inherit",
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+    "tag-storage",
+    "tag-ga4",
+    "tag-potions",
+    "tag-resonance",
+    "tag-neuron",
+    "? ?}&?#??X\b",
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+  },
+  {
+   "id": "q27",
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+   "query": "Grandma Lucas stroke February 2006 goodbye window",
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+    "bl-4476e856-c567-4b49-8ff7-d7dca3e5715e",
+    "tag-upload-window",
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+  },
+  {
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+  },
+  {
+   "id": "q29",
+   "category": "associative",
+   "query": "Sarah Bishop Dyer trailer performance",
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+    "kn-eb1c6d99-d603-4f33-be9a-c63a178690c6",
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+    "mem-89c02aae-d3ca-43f9-9e5d-eb369896276c",
+    "tag-sarah",
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q30",
+   "category": "associative",
+   "query": "Swarm Architecture containment lateral worker",
+   "returned": [
+    "mem-265a7107-73b3-4410-9aff-43787d5f473b",
+    "mem-9d1bf963-1b40-4588-bdb3-0432646cc623",
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+    "bl-e0a0df72-de6e-46ab-800b-e1e3e8dfc387",
+    "tag-__patents____swarm____claim-language____prior-art____filing__",
+    "mem-ab34c2f7-3243-424b-affa-25555f6cf9cc",
+    "? ?}&?#??X\b",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "7?e?7???\f3?"
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+  },
+  {
+   "id": "q31",
+   "category": "associative",
+   "query": "hope won inside the narrative preface",
+   "returned": [
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+    "bl-e148d23c-24e8-4122-9915-d1c11f22052f",
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+    "mem-22f5f665-3ad2-4063-88b0-915849a795f5",
+    "tag-dark-theme",
+    "? ?}&?#??X\b",
+    "art-ddfcd045-2c3b-4a1e-9966-fec5ce44e1dd",
+    "?Q??m?;��`'",
+    "R^??m?;��?'"
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q32",
+   "category": "associative",
+   "query": "man of the house six years old expectation",
+   "returned": [
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+    "bl-ffa22d7e-42a9-4bd2-a428-1d2df243ac93",
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+    "bl-4a6746e8-191f-48fc-8bfb-c4dc73b80bcd",
+    "tag-withholding",
+    "tag-offline",
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+    "art-2fabd873-d787-49cb-ad30-d4ed9fcff8ef",
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+  },
+  {
+   "id": "q33",
+   "category": "nonsense",
+   "query": "zqxjvw plimforth grebulon",
+   "returned": [],
+   "n_returned": 0,
+   "latency_ms": 1318.6,
+   "error": null,
+   "clean": true,
+   "false_positives": 0
+  },
+  {
+   "id": "q34",
+   "category": "nonsense",
+   "query": "flarnbistle quommetry",
+   "returned": [],
+   "n_returned": 0,
+   "latency_ms": 875.7,
+   "error": null,
+   "clean": true,
+   "false_positives": 0
+  },
+  {
+   "id": "q35",
+   "category": "nonsense",
+   "query": "xxqzzt vurblenacht throom",
+   "returned": [
+    "kn-333542cb-6dab-4662-9725-bf7440d28bf7",
+    "? ?}&?#??X\b",
+    "art-ddfcd045-2c3b-4a1e-9966-fec5ce44e1dd",
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+   "error": null,
+   "clean": false,
+   "false_positives": 8
+  },
+  {
+   "id": "q36",
+   "category": "superseded",
+   "query": "is the self-improvement architecture called DARMA or DHARMA",
+   "returned": [
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+    "ctx-e5427d7d",
+    "project-worldweaver",
+    "tag-__kotlin____internal-state____pre-reasoning____post-reasoning____compression-ratio____dharma____cultivation__",
+    "tag-import",
+    "tag-enterprise",
+    "tag-__cgi____dharma____cultivation____five-primitives____seed-artifact____agi____intelligence____whitepaper____patent__",
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+    "? ?}&?#??X\b",
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+   "rank_correct": null,
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+  {
+   "id": "q37",
+   "category": "superseded",
+   "query": "how many provisional patents does Will actually have",
+   "returned": [
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+    "art-7bdaff30-5af9-4f0a-93b1-751686f9de3d",
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+    "mem-32203649-3213-4d6d-86fd-3d657ac70d77",
+    "? ?}&?#??X\b",
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+   "id": "q38",
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+    "project-Imprint__discovery__objection_handling__deal_strategy__pipeline__closing_",
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+    "tag-divisors",
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+    "???Ͼd??W\b?"
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+}

tools/retrieval-eval/results-assoc-leg-r2.json

@@ -0,0 +1,956 @@
+{
+ "label": "assoc-leg-r2",
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+ "soul_md5": "ab9d490ecdfb1f9e6f23cca841ad8fb5",
+ "corpus": "/Users/timlingo/neuron-eval-corpora/snapshot-pre-repair-20260806-embedded.json",
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+  {
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+    "imp-dce1da0f-8776-4a9e-972b-33411a7ca138",
+    "a1000001-0000-0000-0000-000000000001",
+    "knw-729fc901-8335-44c4-9f3a-b150b4aa0915",
+    "kn-5b606390-a52d-4ca2-8e0e-eba141d13440",
+    "ctx-175f"
+   ],
+   "n_returned": 9,
+   "latency_ms": 1440.7,
+   "error": null,
+   "hit@5": 0.0,
+   "recall@5": 0.0,
+   "recall@10": 0.0,
+   "precision@5": 0.0,
+   "mrr@10": 0.0
+  },
+  {
+   "id": "q19",
+   "category": "paraphrase",
+   "query": "learning is the wealth creditors cannot seize",
+   "returned": [
+    "knw-e24d6339-5ff3-4bed-ba53-707ffd0dc70a",
+    "knw-ed33e669-0790-44cb-a036-958d605c6fea",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "knw-0087493b-25cd-45b0-bf46-c078c5b49718",
+    "knw-7902acca-604e-409b-8faf-ad85424211d0",
+    "knw-23c27d3b-e0d2-43a8-a80c-0a44477ae18a",
+    "kn-57b4c5e7-40c6-4c90-bf14-71841b0081d4",
+    "8cbb60c5-4999-4ec1-8682-2592aedc4249",
+    "kn-5584ef9c-7f9d-4d7c-a10a-4ee6bc5cf356",
+    "knw-920c891f-bb8c-48c4-9afc-018ef12dcdc4"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1316.5,
+   "error": null,
+   "hit@5": 0.0,
+   "recall@5": 0.0,
+   "recall@10": 0.0,
+   "precision@5": 0.0,
+   "mrr@10": 0.0
+  },
+  {
+   "id": "q20",
+   "category": "paraphrase",
+   "query": "reliability proven by track record not assertion",
+   "returned": [
+    "? ?}&?#??X\b",
+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40",
+    "? ?}&?#??X\b",
+    "knw-f671966c-3387-4848-abca-b5deec122e00",
+    "? ?}&?#??X\b",
+    "a708dd6e-fe73-4f2f-a21e-89daa0985487",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "7?e?7???\f3?"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1620.6,
+   "error": null,
+   "hit@5": 1.0,
+   "recall@5": 1.0,
+   "recall@10": 1.0,
+   "precision@5": 0.2,
+   "mrr@10": 0.5
+  },
+  {
+   "id": "q21",
+   "category": "paraphrase",
+   "query": "boundaries that enable instead of confine",
+   "returned": [
+    "? ?}&?#??X\b",
+    "kn-a5b3d0ac-f6a1-49a4-aebb-b8b4cd67fe83",
+    "? ?}&?#??X\b",
+    "project-Source_kn-6f248a50__Add_containment_rules__convergence__location-independence__failure_modes_",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "kn-5584ef9c-7f9d-4d7c-a10a-4ee6bc5cf356",
+    "ԍ????X????",
+    "??????X??2c",
+    "dR????X?-?S"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1393.5,
+   "error": null,
+   "hit@5": 1.0,
+   "recall@5": 1.0,
+   "recall@10": 1.0,
+   "precision@5": 0.2,
+   "mrr@10": 0.5
+  },
+  {
+   "id": "q22",
+   "category": "paraphrase",
+   "query": "what shifts tells you where to cut a system apart",
+   "returned": [
+    "7?e?7???\f3?",
+    "knw-9e74ee95-ba7d-49b1-9262-977eae9729d1",
+    "kn-f8974b26-78a6-4aad-b893-19a73b20013d",
+    "kn-9397c74b-35f3-4428-b4b0-5123353bbcd1",
+    "?of?7???",
+    "dR????X?-?S",
+    "dz????Xƹ?i",
+    "ԍ????X????",
+    "??????X??2c",
+    "kn-d7c1e0fb-fa59-46d3-b4c9-a0d1d437a491"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1676.1,
+   "error": null,
+   "hit@5": 0.0,
+   "recall@5": 0.0,
+   "recall@10": 0.0,
+   "precision@5": 0.0,
+   "mrr@10": 0.0
+  },
+  {
+   "id": "q23",
+   "category": "paraphrase",
+   "query": "a mind that compounds instead of resetting each day",
+   "returned": [
+    "kn-5584ef9c-7f9d-4d7c-a10a-4ee6bc5cf356",
+    "mem-b43f6ef4-2f5a-418d-b5ce-3f21520cf6b8",
+    "????7???Ջ3",
+    "a1000001-0000-0000-0000-000000000001",
+    "?ǚ?7??????",
+    "mem-024598a9-ed2e-4eeb-b1e1-5410856ff132",
+    "7?e?7???\f3?",
+    "mem-ade9440f-f161-4c18-9b35-1976257e6ebb",
+    "?of?7???",
+    "ea95f600-8dfd-4c7e-b077-a93dc3cd3623"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1534.8,
+   "error": null,
+   "hit@5": 0.0,
+   "recall@5": 0.0,
+   "recall@10": 0.0,
+   "precision@5": 0.0,
+   "mrr@10": 0.0
+  },
+  {
+   "id": "q24",
+   "category": "paraphrase",
+   "query": "loved for the unedited self and not the polished exterior",
+   "returned": [
+    "mem-bbb126a1-b297-42bb-86be-796871829c94",
+    "mem-45022957-2d78-48aa-a714-16d6eca52e0f",
+    "art-4a99aa1a-489b-4b43-958b-25217adb1aad",
+    "knw-35940684-abc4-42f0-b942-818f66b1f69a",
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "art-0f0277a1-4a8e-4645-95dd-fa379976f31c",
+    "art-ddfcd045-2c3b-4a1e-9966-fec5ce44e1dd",
+    "7?e?7???\f3?",
+    "? ?}&?#??X\b",
+    "'?T?a\"B~-?8"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1567.2,
+   "error": null,
+   "hit@5": 0.0,
+   "recall@5": 0.0,
+   "recall@10": 0.0,
+   "precision@5": 0.0,
+   "mrr@10": 0.0
+  },
+  {
+   "id": "q25",
+   "category": "paraphrase",
+   "query": "cheerfulness you arrive at instead of assuming",
+   "returned": [
+    "?ǚ?7??????",
+    "knw-08559f5c-2306-4220-a146-398c74f1643c",
+    "015644f5-8194-4af0-800d-dd4a0cd71396",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "knw-d357b6bb-ad8a-4791-b516-426aea45fa5b",
+    "7?e?7???\f3?",
+    "ctx-bb74",
+    "??S?7???",
+    "knw-f671966c-3387-4848-abca-b5deec122e00"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1280.4,
+   "error": null,
+   "hit@5": 0.0,
+   "recall@5": 0.0,
+   "recall@10": 0.0,
+   "precision@5": 0.0,
+   "mrr@10": 0.0
+  },
+  {
+   "id": "q26",
+   "category": "paraphrase",
+   "query": "a childhood offering no solid foundation to inherit",
+   "returned": [
+    "? ?}&?#??X\b",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "? ?}&?#??X\b",
+    "kn-6061318f-046b-4935-907d-8eafdce14930",
+    "? ?}&?#??X\b",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "kn-0bb4f021-56de-4947-a35b-a37209e7ba21",
+    "7?e?7???\f3?",
+    "mem-7b74cac0-905f-4c35-9688-fbcce105a177"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1401.6,
+   "error": null,
+   "hit@5": 1.0,
+   "recall@5": 1.0,
+   "recall@10": 1.0,
+   "precision@5": 0.2,
+   "mrr@10": 0.25
+  },
+  {
+   "id": "q27",
+   "category": "associative",
+   "query": "Grandma Lucas stroke February 2006 goodbye window",
+   "returned": [
+    "? ?}&?#??X\b",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "? ?}&?#??X\b",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "? ?}&?#??X\b",
+    "kn-0bb4f021-56de-4947-a35b-a37209e7ba21",
+    "? ?}&?#??X\b",
+    "kn-e0423482-cfa5-4796-8689-8495c93b66bc"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1512.2,
+   "error": null,
+   "hit@5": 1.0,
+   "recall@5": 0.09090909090909091,
+   "recall@10": 0.36363636363636365,
+   "precision@5": 0.2,
+   "mrr@10": 0.2
+  },
+  {
+   "id": "q28",
+   "category": "associative",
+   "query": "Marines hernia sepsis medical ward",
+   "returned": [
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "54608b69-78b6-4239-b60f-b8206cfecacc",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "bl-33ecccc2-e37f-43db-91b3-c2a86f08aaac",
+    "015644f5-8194-4af0-800d-dd4a0cd71396",
+    "art-ddfcd045-2c3b-4a1e-9966-fec5ce44e1dd",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "art-e0bdf5d8-d163-491f-b649-453fee8b721d",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1165.2,
+   "error": null,
+   "hit@5": 1.0,
+   "recall@5": 0.07692307692307693,
+   "recall@10": 0.3076923076923077,
+   "precision@5": 0.2,
+   "mrr@10": 0.25
+  },
+  {
+   "id": "q29",
+   "category": "associative",
+   "query": "Sarah Bishop Dyer trailer performance",
+   "returned": [
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "? ?}&?#??X\b",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "? ?}&?#??X\b",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "? ?}&?#??X\b",
+    "015644f5-8194-4af0-800d-dd4a0cd71396",
+    "art-4a99aa1a-489b-4b43-958b-25217adb1aad",
+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1230.6,
+   "error": null,
+   "hit@5": 1.0,
+   "recall@5": 0.09090909090909091,
+   "recall@10": 0.36363636363636365,
+   "precision@5": 0.2,
+   "mrr@10": 0.25
+  },
+  {
+   "id": "q30",
+   "category": "associative",
+   "query": "Swarm Architecture containment lateral worker",
+   "returned": [
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "bl-9bde67c1-f0ba-4c3a-8fe5-de0deee0ce43",
+    "ctx-e5427d7d",
+    "kn-b36902cc-0b05-44ba-9aa7-800e5dea9ca9",
+    "ctx-bb74",
+    "8cbb60c5-4999-4ec1-8682-2592aedc4249",
+    "kn-6f248a50-355b-47bb-aec8-e0e646a9b077",
+    "kn-5adecd7e-d6db-4576-87fe-6ef8a935cea6",
+    "bl-0fac287f-f4c0-4f15-bc4d-ff7f8a7af3ae",
+    "bl-8c2d5f51-3ccd-4c2e-848a-eb60d90a3b98"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1223.5,
+   "error": null,
+   "hit@5": 0.0,
+   "recall@5": 0.0,
+   "recall@10": 0.0,
+   "precision@5": 0.0,
+   "mrr@10": 0.0
+  },
+  {
+   "id": "q31",
+   "category": "associative",
+   "query": "hope won inside the narrative preface",
+   "returned": [
+    "kn-e0423482-cfa5-4796-8689-8495c93b66bc",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "bl-2b00aeb0-c0fa-4a9f-8f30-4207e98b3d52",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "kn-5b606390-a52d-4ca2-8e0e-eba141d13440",
+    "knw-4aebd815-4eaf-49d7-954b-03595f3d48be",
+    "kn-13f60407-7b70-4db1-964f-ea1f8196efbd",
+    "knw-9e74ee95-ba7d-49b1-9262-977eae9729d1",
+    "knw-d357b6bb-ad8a-4791-b516-426aea45fa5b"
+   ],
+   "n_returned": 9,
+   "latency_ms": 1235.8,
+   "error": null,
+   "hit@5": 1.0,
+   "recall@5": 0.18181818181818182,
+   "recall@10": 0.18181818181818182,
+   "precision@5": 0.4,
+   "mrr@10": 0.5
+  },
+  {
+   "id": "q32",
+   "category": "associative",
+   "query": "man of the house six years old expectation",
+   "returned": [
+    "? ?}&?#??X\b",
+    "4f698ae6-c40e-464e-9798-50350991a188",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "kn-6061318f-046b-4935-907d-8eafdce14930",
+    "? ?}&?#??X\b",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "? ?}&?#??X\b",
+    "kn-0bb4f021-56de-4947-a35b-a37209e7ba21",
+    "? ?}&?#??X\b",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1460.4,
+   "error": null,
+   "hit@5": 0.0,
+   "recall@5": 0.0,
+   "recall@10": 0.2727272727272727,
+   "precision@5": 0.0,
+   "mrr@10": 0.16666666666666666
+  },
+  {
+   "id": "q33",
+   "category": "nonsense",
+   "query": "zqxjvw plimforth grebulon",
+   "returned": [],
+   "n_returned": 0,
+   "latency_ms": 750.0,
+   "error": null,
+   "clean": true,
+   "false_positives": 0
+  },
+  {
+   "id": "q34",
+   "category": "nonsense",
+   "query": "flarnbistle quommetry",
+   "returned": [],
+   "n_returned": 0,
+   "latency_ms": 531.1,
+   "error": null,
+   "clean": true,
+   "false_positives": 0
+  },
+  {
+   "id": "q35",
+   "category": "nonsense",
+   "query": "xxqzzt vurblenacht throom",
+   "returned": [
+    "art-4a99aa1a-489b-4b43-958b-25217adb1aad",
+    "?V?",
+    "knw-6b48dce2-f21c-452a-9db5-4e6aa61c87ca",
+    "knw-920c891f-bb8c-48c4-9afc-018ef12dcdc4",
+    "?m?\\}Q??6??",
+    "8cbb60c5-4999-4ec1-8682-2592aedc4249",
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "?m?\\}Q??6??",
+    "knw-723551f5-1950-42a3-8b89-b6a06913cef0",
+    "art-ddfcd045-2c3b-4a1e-9966-fec5ce44e1dd"
+   ],
+   "n_returned": 10,
+   "latency_ms": 769.1,
+   "error": null,
+   "clean": false,
+   "false_positives": 10
+  },
+  {
+   "id": "q36",
+   "category": "superseded",
+   "query": "is the self-improvement architecture called DARMA or DHARMA",
+   "returned": [
+    "7?e?7???\f3?",
+    "mem-80d7416b-20e9-48a0-b176-b215527e2f56",
+    "? ?}&?#??X\b",
+    "mem-f3b37427-b7d1-4f7e-b32c-0241a20ce8da",
+    "? ?}&?#??X\b",
+    "kn-b7e98d63-8b83-4911-b4d0-990602a7f575",
+    "?of?7???",
+    "knw-e047bb42-dc5b-4383-9e88-e508dc03abe3",
+    "? ?}&?#??X\b",
+    "bl-5b17bd3b-0c41-46cb-a710-6fa4429692ff"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1327.8,
+   "error": null,
+   "hit@5": 1.0,
+   "recall@5": 1.0,
+   "recall@10": 1.0,
+   "precision@5": 0.2,
+   "mrr@10": 0.5,
+   "outranks": true,
+   "rank_correct": 2,
+   "rank_stale": 10
+  },
+  {
+   "id": "q37",
+   "category": "superseded",
+   "query": "how many provisional patents does Will actually have",
+   "returned": [
+    "? ?}&?#??X\b",
+    "12082f7e-e320-438b-bd65-083d8259748f",
+    "? ?}&?#??X\b",
+    "527ecb25-2587-47eb-8269-73be2431abd4",
+    "? ?}&?#??X\b",
+    "3cf706a1-3825-45d8-b0a9-06cae6cdf5b8",
+    "? ?}&?#??X\b",
+    "4f698ae6-c40e-464e-9798-50350991a188",
+    "? ?}&?#??X\b",
+    "be3b6036-6eca-44a7-8fdf-37b23edfdfd1"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1687.3,
+   "error": null,
+   "hit@5": 0.0,
+   "recall@5": 0.0,
+   "recall@10": 1.0,
+   "precision@5": 0.0,
+   "mrr@10": 0.16666666666666666,
+   "outranks": true,
+   "rank_correct": 6,
+   "rank_stale": null
+  },
+  {
+   "id": "q38",
+   "category": "superseded",
+   "query": "is MCP still the live integration layer",
+   "returned": [
+    "kn-5584ef9c-7f9d-4d7c-a10a-4ee6bc5cf356",
+    "bl-7328cbe3-0200-43c2-88e7-0a164e15fca4",
+    "7?e?7???\f3?",
+    "mem-101e81b4-8097-4749-8d8d-7bb66de34517",
+    "? ?}&?#??X\b",
+    "4509ed62-9fb2-48b8-9038-ac569fca9604",
+    "%???2??jH??",
+    "art-8a0870d5-a716-4672-8094-f7463af1265b",
+    "???Ͼd??W\b?",
+    "bl-556438af-57b2-4bd8-a747-9f868aaee290"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1040.6,
+   "error": null,
+   "hit@5": 0.0,
+   "recall@5": 0.0,
+   "recall@10": 0.0,
+   "precision@5": 0.0,
+   "mrr@10": 0.0,
+   "outranks": false,
+   "rank_correct": null,
+   "rank_stale": 4
+  }
+ ]
+}

tools/retrieval-eval/results-assoc-leg.json

@@ -0,0 +1,956 @@
+{
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+   "id": "q21",
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+   "returned": [
+    "? ?}&?#??X\b",
+    "kn-a5b3d0ac-f6a1-49a4-aebb-b8b4cd67fe83",
+    "? ?}&?#??X\b",
+    "project-Source_kn-6f248a50__Add_containment_rules__convergence__location-independence__failure_modes_",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "kn-5584ef9c-7f9d-4d7c-a10a-4ee6bc5cf356",
+    "ԍ????X????",
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+  {
+   "id": "q22",
+   "category": "paraphrase",
+   "query": "what shifts tells you where to cut a system apart",
+   "returned": [
+    "7?e?7???\f3?",
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+    "kn-f8974b26-78a6-4aad-b893-19a73b20013d",
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+    "ԍ????X????",
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+  {
+   "id": "q23",
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+   "query": "a mind that compounds instead of resetting each day",
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+  {
+   "id": "q24",
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+   "id": "q25",
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+  {
+   "id": "q26",
+   "category": "paraphrase",
+   "query": "a childhood offering no solid foundation to inherit",
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+    "? ?}&?#??X\b",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "? ?}&?#??X\b",
+    "kn-6061318f-046b-4935-907d-8eafdce14930",
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+  },
+  {
+   "id": "q27",
+   "category": "associative",
+   "query": "Grandma Lucas stroke February 2006 goodbye window",
+   "returned": [
+    "? ?}&?#??X\b",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "? ?}&?#??X\b",
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+    "? ?}&?#??X\b",
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+  {
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+   "query": "Sarah Bishop Dyer trailer performance",
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+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
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+   "mrr@10": 0.25
+  },
+  {
+   "id": "q30",
+   "category": "associative",
+   "query": "Swarm Architecture containment lateral worker",
+   "returned": [
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+    "bl-9bde67c1-f0ba-4c3a-8fe5-de0deee0ce43",
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+  {
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+   "query": "hope won inside the narrative preface",
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+   "mrr@10": 0.5
+  },
+  {
+   "id": "q32",
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+   "query": "man of the house six years old expectation",
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+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
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+    "? ?}&?#??X\b",
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+  {
+   "id": "q33",
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+   "query": "zqxjvw plimforth grebulon",
+   "returned": [],
+   "n_returned": 0,
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+   "error": null,
+   "clean": true,
+   "false_positives": 0
+  },
+  {
+   "id": "q34",
+   "category": "nonsense",
+   "query": "flarnbistle quommetry",
+   "returned": [],
+   "n_returned": 0,
+   "latency_ms": 519.1,
+   "error": null,
+   "clean": true,
+   "false_positives": 0
+  },
+  {
+   "id": "q35",
+   "category": "nonsense",
+   "query": "xxqzzt vurblenacht throom",
+   "returned": [
+    "art-4a99aa1a-489b-4b43-958b-25217adb1aad",
+    "?V?",
+    "knw-6b48dce2-f21c-452a-9db5-4e6aa61c87ca",
+    "knw-920c891f-bb8c-48c4-9afc-018ef12dcdc4",
+    "?m?\\}Q??6??",
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+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "?m?\\}Q??6??",
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+  },
+  {
+   "id": "q36",
+   "category": "superseded",
+   "query": "is the self-improvement architecture called DARMA or DHARMA",
+   "returned": [
+    "7?e?7???\f3?",
+    "mem-80d7416b-20e9-48a0-b176-b215527e2f56",
+    "? ?}&?#??X\b",
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+    "? ?}&?#??X\b",
+    "kn-b7e98d63-8b83-4911-b4d0-990602a7f575",
+    "?of?7???",
+    "knw-e047bb42-dc5b-4383-9e88-e508dc03abe3",
+    "? ?}&?#??X\b",
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+   "rank_correct": 2,
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+  },
+  {
+   "id": "q37",
+   "category": "superseded",
+   "query": "how many provisional patents does Will actually have",
+   "returned": [
+    "? ?}&?#??X\b",
+    "12082f7e-e320-438b-bd65-083d8259748f",
+    "? ?}&?#??X\b",
+    "527ecb25-2587-47eb-8269-73be2431abd4",
+    "? ?}&?#??X\b",
+    "3cf706a1-3825-45d8-b0a9-06cae6cdf5b8",
+    "? ?}&?#??X\b",
+    "4f698ae6-c40e-464e-9798-50350991a188",
+    "? ?}&?#??X\b",
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+  {
+   "id": "q38",
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+   "query": "is MCP still the live integration layer",
+   "returned": [
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+    "bl-7328cbe3-0200-43c2-88e7-0a164e15fca4",
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+    "4509ed62-9fb2-48b8-9038-ac569fca9604",
+    "%???2??jH??",
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+    "???Ͼd??W\b?",
+    "bl-556438af-57b2-4bd8-a747-9f868aaee290"
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+  }
+ ]
+}

tools/retrieval-eval/results-baseline-embcorpus.json

@@ -0,0 +1,945 @@
+{
+ "label": "baseline-embcorpus",
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+ "soul_md5": "5cc9521734907cf2da30f0af94498c06",
+ "corpus": "/private/tmp/claude-501/-Users-timlingo/82369039-a20e-4b5a-8a5e-28234a57b996/scratchpad/corpus-embedded.json",
+ "corpus_nodes": 78768,
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+ "gold_set": "/Users/timlingo/Development/neuron-technologies/_wt-eval/tools/retrieval-eval/gold_set.json",
+ "limit": 10,
+ "port": 7893,
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+ "child_pid": 85995,
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+   "id": "q01",
+   "category": "exact_rare",
+   "query": "unjailbreakable",
+   "returned": [
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+  },
+  {
+   "id": "q02",
+   "category": "exact_rare",
+   "query": "engram-migrate",
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+   ],
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+  },
+  {
+   "id": "q03",
+   "category": "exact_rare",
+   "query": "cartabandonedevent",
+   "returned": [
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+  },
+  {
+   "id": "q04",
+   "category": "exact_rare",
+   "query": "pre-apprenticeship",
+   "returned": [
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+  },
+  {
+   "id": "q05",
+   "category": "exact_rare",
+   "query": "inferencenodemanager",
+   "returned": [
+    "mem-73969486-143f-4431-b5e6-6845d1cc9848"
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+  },
+  {
+   "id": "q06",
+   "category": "exact_rare",
+   "query": "clear-eyed",
+   "returned": [
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+   "mrr@10": 1.0
+  },
+  {
+   "id": "q07",
+   "category": "phrase",
+   "query": "patterns not returns",
+   "returned": [
+    "kn-57b4c5e7-40c6-4c90-bf14-71841b0081d4",
+    "?ǚ?7??????",
+    "mem-a4a9dfc3-e40b-49b3-b1e1-060e8be2f482",
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+    "art-d24fd6dd-2cda-4eed-92f3-67b535a0d71b",
+    "7?e?7???\f3?"
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+  {
+   "id": "q08",
+   "category": "phrase",
+   "query": "thirty moves",
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+    "knw-e94982a2-358d-4f2f-af31-8ee0fcec07c6",
+    "Z[?<S???H??",
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+    "kn-6061318f-046b-4935-907d-8eafdce14930"
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+  },
+  {
+   "id": "q09",
+   "category": "phrase",
+   "query": "Grandma Lucas",
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+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
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+    "art-79042b8b-6192-440f-90b0-60708f7e6325"
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+  },
+  {
+   "id": "q10",
+   "category": "phrase",
+   "query": "Directed Harmonic",
+   "returned": [
+    "kn-5584ef9c-7f9d-4d7c-a10a-4ee6bc5cf356",
+    "ԍ????X????",
+    "bl-dcee1887-34c4-4ffa-9119-1e291685ba08",
+    "?ǚ?7??????",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "knw-e24d6339-5ff3-4bed-ba53-707ffd0dc70a",
+    "mem-7eeacad7-d7c2-4c2b-8348-19a59aa6dbaf",
+    "????7???Ջ3",
+    "??????X??2c",
+    "g?e?7???'c?"
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+  {
+   "id": "q11",
+   "category": "phrase",
+   "query": "Sarah Bishop",
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+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "art-ddfcd045-2c3b-4a1e-9966-fec5ce44e1dd",
+    "? ?}&?#??X\b",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "766de879-f9d0-4a07-b6df-b43ee13763d8",
+    "mem-a9a9ce95-0d64-46eb-9db8-ff81d78ade35",
+    "mem-b8ecd23e-77ce-42f7-984c-f51453fec16d"
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+  },
+  {
+   "id": "q12",
+   "category": "phrase",
+   "query": "Directed Autonomous Runtime Modification",
+   "returned": [
+    "bl-5b17bd3b-0c41-46cb-a710-6fa4429692ff",
+    "bl-145a0985-2382-400f-a7c5-c335c5e30a72",
+    "mem-82b93b21-a865-410f-9ec1-fc54121d9bb5",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "mem-e6327f52-2bda-4ce7-9471-2fffd1e172de",
+    "7?e?7???\f3?",
+    "?of?7???",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b"
+   ],
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+  },
+  {
+   "id": "q13",
+   "category": "phrase",
+   "query": "zero-knowledge encrypted backup",
+   "returned": [
+    "7774a16c-1027-4e3b-a21e-67f1f95a4acd",
+    "deda48cd-5e1a-46cb-bd43-8016afdb3a8a",
+    "mem-dba009a2-d2ea-4f5a-b9e8-0f04bc9ab32f",
+    "mem-a3c97012-5fa3-4915-a839-2c75c72005e0",
+    "mem-7cd90611-88a3-423d-a38a-0db2812952fa",
+    "bl-07375bf9-a169-42cd-adb3-7d32b25982f0",
+    "bl-ec84b63d-b278-4944-8d7f-4aa7a51c0315",
+    "7?e?7???\f3?",
+    "?of?7???",
+    "? ?}&?#??X\b"
+   ],
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+  },
+  {
+   "id": "q14",
+   "category": "paraphrase",
+   "query": "the elderly relative who passed while he stayed away",
+   "returned": [
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "art-4a99aa1a-489b-4b43-958b-25217adb1aad",
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "????7???Ջ3",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "art-0f0277a1-4a8e-4645-95dd-fa379976f31c"
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+  },
+  {
+   "id": "q15",
+   "category": "paraphrase",
+   "query": "a soldier sidelined by illness who refused to quit",
+   "returned": [
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "art-2fabd873-d787-49cb-ad30-d4ed9fcff8ef",
+    "art-2f29ad36-6ee6-4a0e-8d72-0eaf7d12d3a9",
+    "? ?}&?#??X\b",
+    "kn-a31e1001-342e-4deb-a2e6-6d02d1f22dee",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "knw-9e74ee95-ba7d-49b1-9262-977eae9729d1",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b"
+   ],
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+  },
+  {
+   "id": "q16",
+   "category": "paraphrase",
+   "query": "choosing an uncomfortable fact over a pleasant fiction",
+   "returned": [
+    "7?e?7???\f3?",
+    "? ?}&?#??X\b",
+    "kn-f8974b26-78a6-4aad-b893-19a73b20013d",
+    "?of?7???",
+    "????7???Ջ3",
+    "kn-d97920d0-1649-4223-9508-c0bb621e7fc0",
+    "kn-57b4c5e7-40c6-4c90-bf14-71841b0081d4",
+    "kn-9397c74b-35f3-4428-b4b0-5123353bbcd1",
+    "kn-81c24d13-a73b-4767-819c-dafaacc1498e",
+    "? ?}&?#??X\b"
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+  },
+  {
+   "id": "q17",
+   "category": "paraphrase",
+   "query": "a tight payload beats a bloated one",
+   "returned": [
+    "kn-d7c1e0fb-fa59-46d3-b4c9-a0d1d437a491",
+    "7?e?7???\f3?",
+    "? ?}&?#??X\b",
+    "kn-e8423822-eacf-4029-aa7b-10d4d28d621e",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "??o?'?B???k",
+    "kn-9397c74b-35f3-4428-b4b0-5123353bbcd1",
+    "? ?}&?#??X\b",
+    "?of?7???"
+   ],
+   "n_returned": 10,
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q18",
+   "category": "paraphrase",
+   "query": "if you are able and nobody is coming the job is yours",
+   "returned": [
+    "7?e?7???\f3?",
+    "?of?7???",
+    "imp-dce1da0f-8776-4a9e-972b-33411a7ca138",
+    "kn-5b606390-a52d-4ca2-8e0e-eba141d13440",
+    "kn-83bb86c6-521d-416c-a86e-6e29c2d8f102",
+    "kn-f8974b26-78a6-4aad-b893-19a73b20013d",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b"
+   ],
+   "n_returned": 9,
+   "latency_ms": 1350.4,
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q19",
+   "category": "paraphrase",
+   "query": "learning is the wealth creditors cannot seize",
+   "returned": [
+    "kn-5584ef9c-7f9d-4d7c-a10a-4ee6bc5cf356",
+    "knw-7902acca-604e-409b-8faf-ad85424211d0",
+    "knw-e24d6339-5ff3-4bed-ba53-707ffd0dc70a",
+    "kn-57b4c5e7-40c6-4c90-bf14-71841b0081d4",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "7?e?7???\f3?",
+    "??o?'?B???k",
+    "? ?}&?#??X\b",
+    "kn-0625e393-067c-4bba-8389-7e1b79265142",
+    "ע?RGk?\tH(?"
+   ],
+   "n_returned": 10,
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q20",
+   "category": "paraphrase",
+   "query": "reliability proven by track record not assertion",
+   "returned": [
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "7?e?7???\f3?",
+    "?of?7???",
+    "art-2fabd873-d787-49cb-ad30-d4ed9fcff8ef",
+    "kn-5584ef9c-7f9d-4d7c-a10a-4ee6bc5cf356"
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q21",
+   "category": "paraphrase",
+   "query": "boundaries that enable instead of confine",
+   "returned": [
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "??????X??2c",
+    "ԍ????X????",
+    "dR????X?-?S",
+    "kn-5584ef9c-7f9d-4d7c-a10a-4ee6bc5cf356",
+    "dz????Xƹ?i",
+    "kn-d7c1e0fb-fa59-46d3-b4c9-a0d1d437a491"
+   ],
+   "n_returned": 10,
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+   "precision@5": 0.0,
+   "mrr@10": 0.0
+  },
+  {
+   "id": "q22",
+   "category": "paraphrase",
+   "query": "what shifts tells you where to cut a system apart",
+   "returned": [
+    "7?e?7???\f3?",
+    "kn-9397c74b-35f3-4428-b4b0-5123353bbcd1",
+    "?of?7???",
+    "kn-f8974b26-78a6-4aad-b893-19a73b20013d",
+    "knw-9e74ee95-ba7d-49b1-9262-977eae9729d1",
+    "dR????X?-?S",
+    "dz????Xƹ?i",
+    "ԍ????X????",
+    "??????X??2c",
+    "kn-d7c1e0fb-fa59-46d3-b4c9-a0d1d437a491"
+   ],
+   "n_returned": 10,
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q23",
+   "category": "paraphrase",
+   "query": "a mind that compounds instead of resetting each day",
+   "returned": [
+    "?ǚ?7??????",
+    "kn-5584ef9c-7f9d-4d7c-a10a-4ee6bc5cf356",
+    "????7???Ջ3",
+    "7?e?7???\f3?",
+    "? ?}&?#??X\b",
+    "kn-9397c74b-35f3-4428-b4b0-5123353bbcd1",
+    "%???2??jH??",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "?of?7???"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1441.7,
+   "error": null,
+   "hit@5": 0.0,
+   "recall@5": 0.0,
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+   "precision@5": 0.0,
+   "mrr@10": 0.0
+  },
+  {
+   "id": "q24",
+   "category": "paraphrase",
+   "query": "loved for the unedited self and not the polished exterior",
+   "returned": [
+    "mem-bbb126a1-b297-42bb-86be-796871829c94",
+    "mem-45022957-2d78-48aa-a714-16d6eca52e0f",
+    "art-4a99aa1a-489b-4b43-958b-25217adb1aad",
+    "knw-35940684-abc4-42f0-b942-818f66b1f69a",
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "art-0f0277a1-4a8e-4645-95dd-fa379976f31c",
+    "art-ddfcd045-2c3b-4a1e-9966-fec5ce44e1dd",
+    "7?e?7???\f3?",
+    "? ?}&?#??X\b",
+    "'?T?a\"B~-?8"
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+   "id": "q26",
+   "category": "paraphrase",
+   "query": "a childhood offering no solid foundation to inherit",
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+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
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+    "? ?}&?#??X\b",
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+  },
+  {
+   "id": "q29",
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+   "query": "man of the house six years old expectation",
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+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
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+  },
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+   "id": "q33",
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+  {
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+    "knw-920c891f-bb8c-48c4-9afc-018ef12dcdc4",
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+   "query": "is the self-improvement architecture called DARMA or DHARMA",
+   "returned": [
+    "7?e?7???\f3?",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
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+   "query": "how many provisional patents does Will actually have",
+   "returned": [
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+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
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+    "7?e?7???\f3?",
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+ ]
+}

tools/retrieval-eval/results-bm25lex-r2.json

@@ -0,0 +1,959 @@
+{
+ "label": "bm25lex-r2",
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+ "soul_md5": "dfbd0f8e3646212db5c60026f8ad906f",
+ "corpus": "/Users/timlingo/neuron-eval-corpora/snapshot-pre-repair-20260806-embedded.json",
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+ "gold_set": "/Users/timlingo/Development/neuron-technologies/_wt-eval/tools/retrieval-eval/gold_set.json",
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+   "category": "phrase",
+   "query": "Grandma Lucas",
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+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
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+  {
+   "id": "q10",
+   "category": "phrase",
+   "query": "Directed Harmonic",
+   "returned": [
+    "bl-dcee1887-34c4-4ffa-9119-1e291685ba08",
+    "project-harmonic-framework",
+    "bl-798d135f-3987-4ccd-8de6-70ca2f358337",
+    "mem-7eeacad7-d7c2-4c2b-8348-19a59aa6dbaf",
+    "project-harmonic-framework_com",
+    "bl-680b24a9-edc3-4a9d-847a-bff0b46b568c",
+    "tag-harmonic-design",
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+   "id": "q11",
+   "category": "phrase",
+   "query": "Sarah Bishop",
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+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
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+  {
+   "id": "q12",
+   "category": "phrase",
+   "query": "Directed Autonomous Runtime Modification",
+   "returned": [
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+   "category": "phrase",
+   "query": "zero-knowledge encrypted backup",
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+   "category": "paraphrase",
+   "query": "the elderly relative who passed while he stayed away",
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+   "category": "paraphrase",
+   "query": "a soldier sidelined by illness who refused to quit",
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+  {
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+   "category": "paraphrase",
+   "query": "choosing an uncomfortable fact over a pleasant fiction",
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+   "id": "q17",
+   "category": "paraphrase",
+   "query": "a tight payload beats a bloated one",
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+   "category": "paraphrase",
+   "query": "if you are able and nobody is coming the job is yours",
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+  {
+   "id": "q19",
+   "category": "paraphrase",
+   "query": "learning is the wealth creditors cannot seize",
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+  {
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+   "category": "paraphrase",
+   "query": "reliability proven by track record not assertion",
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+   "category": "paraphrase",
+   "query": "boundaries that enable instead of confine",
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+   "category": "paraphrase",
+   "query": "what shifts tells you where to cut a system apart",
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+   "query": "a mind that compounds instead of resetting each day",
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+   "category": "paraphrase",
+   "query": "loved for the unedited self and not the polished exterior",
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+  {
+   "id": "q25",
+   "category": "paraphrase",
+   "query": "cheerfulness you arrive at instead of assuming",
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+   "id": "q26",
+   "category": "paraphrase",
+   "query": "a childhood offering no solid foundation to inherit",
+   "returned": [
+    "bl-3f57bc69-7285-4f4a-a861-2de52efca058",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "kn-f230b362-b201-4402-9833-4160c89ab3d4",
+    "bl-0d8c5dfa-e163-4fef-a58b-56b0d076c5a8",
+    "kn-6061318f-046b-4935-907d-8eafdce14930",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "mem-b99efff0-00e6-40c8-9c5b-730330eef33b",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "kn-5b606390-a52d-4ca2-8e0e-eba141d13440",
+    "tag-childhood"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1342.9,
+   "error": null,
+   "hit@5": 1.0,
+   "recall@5": 1.0,
+   "recall@10": 1.0,
+   "precision@5": 0.2,
+   "mrr@10": 0.2
+  },
+  {
+   "id": "q27",
+   "category": "associative",
+   "query": "Grandma Lucas stroke February 2006 goodbye window",
+   "returned": [
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "bl-33ecccc2-e37f-43db-91b3-c2a86f08aaac",
+    "kn-0bb4f021-56de-4947-a35b-a37209e7ba21",
+    "766de879-f9d0-4a07-b6df-b43ee13763d8",
+    "kn-e0423482-cfa5-4796-8689-8495c93b66bc",
+    "3499d5da-0e9c-4de4-9bc4-8941b14e0b1f",
+    "kn-78db5396-3dbc-4481-bfc7-e4e1422feb1c"
+   ],
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+   "precision@5": 0.4,
+   "mrr@10": 0.5
+  },
+  {
+   "id": "q28",
+   "category": "associative",
+   "query": "Marines hernia sepsis medical ward",
+   "returned": [
+    "bl-33ecccc2-e37f-43db-91b3-c2a86f08aaac",
+    "54608b69-78b6-4239-b60f-b8206cfecacc",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "mem-9110798f-d0cb-4446-bc2a-14f09b6a09e2",
+    "015644f5-8194-4af0-800d-dd4a0cd71396",
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "art-ddfcd045-2c3b-4a1e-9966-fec5ce44e1dd",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71"
+   ],
+   "n_returned": 10,
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+   "error": null,
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+   "precision@5": 0.2,
+   "mrr@10": 0.25
+  },
+  {
+   "id": "q29",
+   "category": "associative",
+   "query": "Sarah Bishop Dyer trailer performance",
+   "returned": [
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "766de879-f9d0-4a07-b6df-b43ee13763d8",
+    "015644f5-8194-4af0-800d-dd4a0cd71396",
+    "tag-trailer-park-paladins",
+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40",
+    "project-trailer-park-paladins",
+    "kn-78db5396-3dbc-4481-bfc7-e4e1422feb1c"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1183.8,
+   "error": null,
+   "hit@5": 1.0,
+   "recall@5": 0.18181818181818182,
+   "recall@10": 0.45454545454545453,
+   "precision@5": 0.4,
+   "mrr@10": 0.5
+  },
+  {
+   "id": "q30",
+   "category": "associative",
+   "query": "Swarm Architecture containment lateral worker",
+   "returned": [
+    "bl-0fac287f-f4c0-4f15-bc4d-ff7f8a7af3ae",
+    "bl-9bde67c1-f0ba-4c3a-8fe5-de0deee0ce43",
+    "bl-2515d870-e35e-443b-ba20-5150bbc73fed",
+    "kn-a5b3d0ac-f6a1-49a4-aebb-b8b4cd67fe83",
+    "kn-b36902cc-0b05-44ba-9aa7-800e5dea9ca9",
+    "bl-bea7473c-c687-414c-9c0b-00c509a616c1",
+    "bl-fc6fcb0b-9e4b-40bf-8e88-dbfe4e27c31a",
+    "kn-6f248a50-355b-47bb-aec8-e0e646a9b077",
+    "kn-6061318f-046b-4935-907d-8eafdce14930",
+    "mem-ab34c2f7-3243-424b-affa-25555f6cf9cc"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1199.4,
+   "error": null,
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+   "recall@5": 0.0,
+   "recall@10": 0.0,
+   "precision@5": 0.0,
+   "mrr@10": 0.0
+  },
+  {
+   "id": "q31",
+   "category": "associative",
+   "query": "hope won inside the narrative preface",
+   "returned": [
+    "kn-e0423482-cfa5-4796-8689-8495c93b66bc",
+    "knw-e94982a2-358d-4f2f-af31-8ee0fcec07c6",
+    "bl-2b00aeb0-c0fa-4a9f-8f30-4207e98b3d52",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "kn-5b606390-a52d-4ca2-8e0e-eba141d13440",
+    "knw-4aebd815-4eaf-49d7-954b-03595f3d48be",
+    "knw-723551f5-1950-42a3-8b89-b6a06913cef0",
+    "tag-hope",
+    "knw-d357b6bb-ad8a-4791-b516-426aea45fa5b",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1202.9,
+   "error": null,
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+   "recall@5": 0.09090909090909091,
+   "recall@10": 0.18181818181818182,
+   "precision@5": 0.2,
+   "mrr@10": 0.25
+  },
+  {
+   "id": "q32",
+   "category": "associative",
+   "query": "man of the house six years old expectation",
+   "returned": [
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "knw-729fc901-8335-44c4-9f3a-b150b4aa0915",
+    "knw-d357b6bb-ad8a-4791-b516-426aea45fa5b",
+    "knw-528dbc37-eabc-4b75-a7a5-65bf38d6018a",
+    "knw-35940684-abc4-42f0-b942-818f66b1f69a",
+    "knw-473f3f24-20f6-4f39-8589-3709538eb6ac",
+    "?Z?<S???K ?",
+    "knw-7902acca-604e-409b-8faf-ad85424211d0",
+    "'?T?a\"B~-?8",
+    "kn-6061318f-046b-4935-907d-8eafdce14930"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1414.1,
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+   "recall@5": 0.0,
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+   "precision@5": 0.0,
+   "mrr@10": 0.0
+  },
+  {
+   "id": "q33",
+   "category": "nonsense",
+   "query": "zqxjvw plimforth grebulon",
+   "returned": [],
+   "n_returned": 0,
+   "latency_ms": 703.0,
+   "error": null,
+   "clean": true,
+   "false_positives": 0
+  },
+  {
+   "id": "q34",
+   "category": "nonsense",
+   "query": "flarnbistle quommetry",
+   "returned": [],
+   "n_returned": 0,
+   "latency_ms": 492.9,
+   "error": null,
+   "clean": true,
+   "false_positives": 0
+  },
+  {
+   "id": "q35",
+   "category": "nonsense",
+   "query": "xxqzzt vurblenacht throom",
+   "returned": [
+    "bl-4476e856-c567-4b49-8ff7-d7dca3e5715e",
+    "?V?",
+    "knw-6b48dce2-f21c-452a-9db5-4e6aa61c87ca",
+    "knw-920c891f-bb8c-48c4-9afc-018ef12dcdc4",
+    "?m?\\}Q??6??",
+    "8cbb60c5-4999-4ec1-8682-2592aedc4249",
+    "kn-66a21179-2adc-4b19-a109-880cf4674d7d",
+    "?m?\\}Q??6??",
+    "knw-723551f5-1950-42a3-8b89-b6a06913cef0",
+    "kn-333542cb-6dab-4662-9725-bf7440d28bf7"
+   ],
+   "n_returned": 10,
+   "latency_ms": 728.4,
+   "error": null,
+   "clean": false,
+   "false_positives": 10
+  },
+  {
+   "id": "q36",
+   "category": "superseded",
+   "query": "is the self-improvement architecture called DARMA or DHARMA",
+   "returned": [
+    "mem-f3b37427-b7d1-4f7e-b32c-0241a20ce8da",
+    "mem-80d7416b-20e9-48a0-b176-b215527e2f56",
+    "tag-__darma____cgi____patents____self-improvement____character-preservation____autonomous____architecture__",
+    "kn-b7e98d63-8b83-4911-b4d0-990602a7f575",
+    "tag-__darma____cgi____patents____self-improvement____character-preservation____autonomous____kotlin____architecture__",
+    "knw-e047bb42-dc5b-4383-9e88-e508dc03abe3",
+    "mem-e6327f52-2bda-4ce7-9471-2fffd1e172de",
+    "bl-5b17bd3b-0c41-46cb-a710-6fa4429692ff",
+    "mem-82b93b21-a865-410f-9ec1-fc54121d9bb5",
+    "bl-145a0985-2382-400f-a7c5-c335c5e30a72"
+   ],
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+   "error": null,
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+   "outranks": true,
+   "rank_correct": 2,
+   "rank_stale": 8
+  },
+  {
+   "id": "q37",
+   "category": "superseded",
+   "query": "how many provisional patents does Will actually have",
+   "returned": [
+    "mem-6f0b2b45-90c1-4356-ac01-3daac05b09c8",
+    "12082f7e-e320-438b-bd65-083d8259748f",
+    "015644f5-8194-4af0-800d-dd4a0cd71396",
+    "13705072-4515-4124-963d-083af490494f",
+    "527ecb25-2587-47eb-8269-73be2431abd4",
+    "6de314bf-5c4c-4cfc-871f-fa2e422d45e6",
+    "a1000001-0000-0000-0000-000000000002",
+    "3cf706a1-3825-45d8-b0a9-06cae6cdf5b8",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "7ac62daa-2eac-4c7a-a97e-e4203fc1b57b"
+   ],
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+   "rank_correct": 8,
+   "rank_stale": null
+  },
+  {
+   "id": "q38",
+   "category": "superseded",
+   "query": "is MCP still the live integration layer",
+   "returned": [
+    "5fcba804-eb5b-48ec-82da-146b1c6bb50d",
+    "bl-7328cbe3-0200-43c2-88e7-0a164e15fca4",
+    "bl-c8c19362-430b-4817-9cf4-9e85e0099c64",
+    "bl-c5c6571e-118f-47c7-8cbb-3ed0ebf64a51",
+    "mem-101e81b4-8097-4749-8d8d-7bb66de34517",
+    "ctx-3a55",
+    "86228228-7adf-41fb-b4c4-9ceea87953ae",
+    "4509ed62-9fb2-48b8-9038-ac569fca9604",
+    "bl-4f7b651b-6b33-449c-8a3b-cfce12ce984b",
+    "mem-3a2cf162-d93b-4f29-86f2-5066fb7fe1f5"
+   ],
+   "n_returned": 10,
+   "latency_ms": 995.5,
+   "error": null,
+   "hit@5": 0.0,
+   "recall@5": 0.0,
+   "recall@10": 0.0,
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+   "mrr@10": 0.0,
+   "outranks": false,
+   "rank_correct": null,
+   "rank_stale": 5
+  }
+ ]
+}

tools/retrieval-eval/results-bm25lex.json

@@ -0,0 +1,959 @@
+{
+ "label": "bm25lex",
+ "soul_binary": "/private/tmp/claude-501/-Users-timlingo/82369039-a20e-4b5a-8a5e-28234a57b996/scratchpad/soul-bm25lex",
+ "soul_md5": "dfbd0f8e3646212db5c60026f8ad906f",
+ "corpus": "/Users/timlingo/neuron-eval-corpora/snapshot-pre-repair-20260806-embedded.json",
+ "corpus_nodes": 78768,
+ "corpus_edges": 14214,
+ "gold_set": "/Users/timlingo/Development/neuron-technologies/_wt-eval/tools/retrieval-eval/gold_set.json",
+ "limit": 10,
+ "port": 7893,
+ "wall_clock_s": 50.4,
+ "child_pid": 90325,
+ "child_confirmed_dead": true,
+ "aggregate": {
+  "n_queries": 38,
+  "n_scored": 35,
+  "hit@5": 0.7428571428571429,
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+  "mrr@10": 0.5021428571428571,
+  "nonsense_clean": "2/3",
+  "superseded_outranks": "2/3",
+  "latency_ms_p50": 1184.4,
+  "latency_ms_p95": 1620.0,
+  "latency_ms_max": 1655.4,
+  "errors": 0,
+  "by_category": {
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+   "exact_rare": {
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+    "recall@10": 1.0,
+    "mrr@10": 1.0
+   },
+   "nonsense": {
+    "n": 3,
+    "clean": 2,
+    "avg_false_positives": 3.3333333333333335
+   },
+   "paraphrase": {
+    "n": 13,
+    "hit@5": 0.6153846153846154,
+    "recall@5": 0.6153846153846154,
+    "recall@10": 0.6153846153846154,
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+   "phrase": {
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+    "hit@5": 1.0,
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+    "outranks": 2
+   }
+  }
+ },
+ "rows": [
+  {
+   "id": "q01",
+   "category": "exact_rare",
+   "query": "unjailbreakable",
+   "returned": [
+    "mem-7f61beb4-271c-4feb-9f6e-1c9c837a6226"
+   ],
+   "n_returned": 1,
+   "latency_ms": 287.7,
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+   "precision@5": 0.2,
+   "mrr@10": 1.0
+  },
+  {
+   "id": "q02",
+   "category": "exact_rare",
+   "query": "engram-migrate",
+   "returned": [
+    "mem-6fdf6545-5e1a-43a9-8bdc-d2cd248146a5",
+    "bl-ba764d70-e9d7-4f62-848f-719cb665f45e",
+    "mem-22fe5ec8-ae0d-4583-a05c-d1ef50353257",
+    "bl-b28d7256-6f74-4567-bd90-40d0ef2a6d78",
+    "project-engram",
+    "ctx-45bc",
+    "project-engram-lang",
+    "ctx-175f",
+    "mem-60778715-758c-4677-933d-fc39b8f94152",
+    "ctx-74ed"
+   ],
+   "n_returned": 10,
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+   "error": null,
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+   "recall@5": 1.0,
+   "recall@10": 1.0,
+   "precision@5": 0.2,
+   "mrr@10": 1.0
+  },
+  {
+   "id": "q03",
+   "category": "exact_rare",
+   "query": "cartabandonedevent",
+   "returned": [
+    "mem-1ba7c67d-85b9-4c2e-9fe2-39f8b0477091"
+   ],
+   "n_returned": 1,
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+   "recall@10": 1.0,
+   "precision@5": 0.2,
+   "mrr@10": 1.0
+  },
+  {
+   "id": "q04",
+   "category": "exact_rare",
+   "query": "pre-apprenticeship",
+   "returned": [
+    "mem-89c02aae-d3ca-43f9-9e5d-eb369896276c"
+   ],
+   "n_returned": 1,
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+   "recall@5": 1.0,
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+   "precision@5": 0.2,
+   "mrr@10": 1.0
+  },
+  {
+   "id": "q05",
+   "category": "exact_rare",
+   "query": "inferencenodemanager",
+   "returned": [
+    "mem-73969486-143f-4431-b5e6-6845d1cc9848",
+    "bl-c1765767-3e27-449a-8c94-10411d1eb7c0",
+    "project-Add_inference_url_config_to_Neuron_MCP__Route_summarization_gen_tasks_to_Pantheon__keep_frontier_for_complex_reasoning_"
+   ],
+   "n_returned": 3,
+   "latency_ms": 304.2,
+   "error": null,
+   "hit@5": 1.0,
+   "recall@5": 1.0,
+   "recall@10": 1.0,
+   "precision@5": 0.2,
+   "mrr@10": 1.0
+  },
+  {
+   "id": "q06",
+   "category": "exact_rare",
+   "query": "clear-eyed",
+   "returned": [
+    "knw-c72597c5-c23d-4c08-8e9e-996dadf26a99"
+   ],
+   "n_returned": 1,
+   "latency_ms": 282.3,
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+   "recall@5": 1.0,
+   "recall@10": 1.0,
+   "precision@5": 0.2,
+   "mrr@10": 1.0
+  },
+  {
+   "id": "q07",
+   "category": "phrase",
+   "query": "patterns not returns",
+   "returned": [
+    "tag-patterns",
+    "mem-a4a9dfc3-e40b-49b3-b1e1-060e8be2f482",
+    "project-Imprint__system_design__ADRs__tech_strategy__integration_patterns__governance_",
+    "project-Imprint__analysis_patterns__data_storytelling__SQL__dashboards__insight_framing_",
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+    "bl-39dad13d-7105-4049-8224-dc3c34fdb1f3",
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+    "bl-7e7c3fdb-4132-487f-aa70-b2cd559cb7f0",
+    "bl-1d32bd54-cf17-4a1f-b235-982d09a36f04",
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+  {
+   "id": "q08",
+   "category": "phrase",
+   "query": "thirty moves",
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+    "knw-7902acca-604e-409b-8faf-ad85424211d0",
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+   "id": "q09",
+   "category": "phrase",
+   "query": "Grandma Lucas",
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+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
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+  {
+   "id": "q10",
+   "category": "phrase",
+   "query": "Directed Harmonic",
+   "returned": [
+    "bl-dcee1887-34c4-4ffa-9119-1e291685ba08",
+    "project-harmonic-framework",
+    "bl-798d135f-3987-4ccd-8de6-70ca2f358337",
+    "mem-7eeacad7-d7c2-4c2b-8348-19a59aa6dbaf",
+    "project-harmonic-framework_com",
+    "bl-680b24a9-edc3-4a9d-847a-bff0b46b568c",
+    "tag-harmonic-design",
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+  {
+   "id": "q11",
+   "category": "phrase",
+   "query": "Sarah Bishop",
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+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
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+    "015644f5-8194-4af0-800d-dd4a0cd71396",
+    "tag-sarah",
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+  {
+   "id": "q12",
+   "category": "phrase",
+   "query": "Directed Autonomous Runtime Modification",
+   "returned": [
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+   "id": "q13",
+   "category": "phrase",
+   "query": "zero-knowledge encrypted backup",
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+    "8f3abb0d-77ed-4af3-9f4d-ba62cd198886",
+    "7774a16c-1027-4e3b-a21e-67f1f95a4acd",
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+  {
+   "id": "q14",
+   "category": "paraphrase",
+   "query": "the elderly relative who passed while he stayed away",
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+   "id": "q15",
+   "category": "paraphrase",
+   "query": "a soldier sidelined by illness who refused to quit",
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+  {
+   "id": "q16",
+   "category": "paraphrase",
+   "query": "choosing an uncomfortable fact over a pleasant fiction",
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+  {
+   "id": "q17",
+   "category": "paraphrase",
+   "query": "a tight payload beats a bloated one",
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+  {
+   "id": "q18",
+   "category": "paraphrase",
+   "query": "if you are able and nobody is coming the job is yours",
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+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
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+  {
+   "id": "q19",
+   "category": "paraphrase",
+   "query": "learning is the wealth creditors cannot seize",
+   "returned": [
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+  {
+   "id": "q20",
+   "category": "paraphrase",
+   "query": "reliability proven by track record not assertion",
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+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40",
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+   "query": "boundaries that enable instead of confine",
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+   "id": "q22",
+   "category": "paraphrase",
+   "query": "what shifts tells you where to cut a system apart",
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+  {
+   "id": "q23",
+   "category": "paraphrase",
+   "query": "a mind that compounds instead of resetting each day",
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+   "id": "q24",
+   "category": "paraphrase",
+   "query": "loved for the unedited self and not the polished exterior",
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+    "knw-729fc901-8335-44c4-9f3a-b150b4aa0915",
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+    "'?T?a\"B~-?8",
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+   "query": "xxqzzt vurblenacht throom",
+   "returned": [
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+    "?V?",
+    "knw-6b48dce2-f21c-452a-9db5-4e6aa61c87ca",
+    "knw-920c891f-bb8c-48c4-9afc-018ef12dcdc4",
+    "?m?\\}Q??6??",
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+    "kn-66a21179-2adc-4b19-a109-880cf4674d7d",
+    "?m?\\}Q??6??",
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+    "mem-80d7416b-20e9-48a0-b176-b215527e2f56",
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+    "12082f7e-e320-438b-bd65-083d8259748f",
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+}

tools/retrieval-eval/results-feat-recall-through-activation.json

@@ -0,0 +1,942 @@
+{
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+  {
+   "id": "q07",
+   "category": "phrase",
+   "query": "patterns not returns",
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+    "kn-69fd6e83-7718-4824-8d66-f49d8954e224",
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+  },
+  {
+   "id": "q08",
+   "category": "phrase",
+   "query": "thirty moves",
+   "returned": [
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+    "knw-2c46cfb4-6d4e-4822-8a1a-7d743c1e4329",
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+    "art-80ca3d31-84dc-4502-83f4-538372b9764f",
+    "?Z?.\f?0?]P?",
+    "?Q??m?;��`'"
+   ],
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+  },
+  {
+   "id": "q09",
+   "category": "phrase",
+   "query": "Grandma Lucas",
+   "returned": [
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "? ?}&?#??X\b",
+    "art-0f0277a1-4a8e-4645-95dd-fa379976f31c",
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+   "mrr@10": 1.0
+  },
+  {
+   "id": "q10",
+   "category": "phrase",
+   "query": "Directed Harmonic",
+   "returned": [
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+    "art-e495c8c5-ad95-4b64-8771-f68aa4cfcd0a",
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+    "kn-9397c74b-35f3-4428-b4b0-5123353bbcd1",
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+    "mem-60778715-758c-4677-933d-fc39b8f94152",
+    "? ?}&?#??X\b",
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+  },
+  {
+   "id": "q11",
+   "category": "phrase",
+   "query": "Sarah Bishop",
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+    "art-79042b8b-6192-440f-90b0-60708f7e6325"
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+  },
+  {
+   "id": "q12",
+   "category": "phrase",
+   "query": "Directed Autonomous Runtime Modification",
+   "returned": [
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+    "mem-46780047-63a0-4a86-a16b-638b72a7fb8d",
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+    "mem-f823e835-313f-4282-b4b3-ce527ffc2f7a",
+    "? ?}&?#??X\b",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "?Z?.\f?0?]P?",
+    "bl-145a0985-2382-400f-a7c5-c335c5e30a72"
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+  },
+  {
+   "id": "q13",
+   "category": "phrase",
+   "query": "zero-knowledge encrypted backup",
+   "returned": [
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+    "bl-e20944e5-eb16-4ab3-a84d-111e0fc817fa",
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+    "mem-47f72b5b-6e8b-4293-94f1-350197b4809a",
+    "mem-e612f0aa-c2f2-4ee3-bbc7-af2dc826233b",
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+    "7774a16c-1027-4e3b-a21e-67f1f95a4acd",
+    "? ?}&?#??X\b",
+    "7?e?7???\f3?",
+    "deda48cd-5e1a-46cb-bd43-8016afdb3a8a"
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+   "n_returned": 10,
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+  },
+  {
+   "id": "q14",
+   "category": "paraphrase",
+   "query": "the elderly relative who passed while he stayed away",
+   "returned": [
+    "kn-82be4e41-96c5-4da3-85c0-cee10763d975",
+    "mem-ea487cb4-ed67-44ce-8402-b56bb28468d4",
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+    "art-0f0277a1-4a8e-4645-95dd-fa379976f31c",
+    "? ?}&?#??X\b",
+    "art-ddfcd045-2c3b-4a1e-9966-fec5ce44e1dd",
+    "art-4a99aa1a-489b-4b43-958b-25217adb1aad"
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+  },
+  {
+   "id": "q15",
+   "category": "paraphrase",
+   "query": "a soldier sidelined by illness who refused to quit",
+   "returned": [
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+    "bl-07375bf9-a169-42cd-adb3-7d32b25982f0",
+    "bl-fd047ce9-ae21-4b3e-b3ab-ece0c9592f7f",
+    "kn-57b4c5e7-40c6-4c90-bf14-71841b0081d4",
+    "bl-6172d035-dd94-4776-afdd-d8915f6fc375",
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+    "art-0f0277a1-4a8e-4645-95dd-fa379976f31c",
+    "art-80ca3d31-84dc-4502-83f4-538372b9764f",
+    "015644f5-8194-4af0-800d-dd4a0cd71396"
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+  },
+  {
+   "id": "q16",
+   "category": "paraphrase",
+   "query": "choosing an uncomfortable fact over a pleasant fiction",
+   "returned": [
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+    "bl-fc893be3-e6b4-4ef6-93b0-d54ca5f89083",
+    "tag-project-structure",
+    "tag-anthropic-contrast",
+    "tag-voice-training",
+    "tag-ebd",
+    "art-80ca3d31-84dc-4502-83f4-538372b9764f",
+    "015644f5-8194-4af0-800d-dd4a0cd71396",
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+    "art-ddfcd045-2c3b-4a1e-9966-fec5ce44e1dd"
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+  },
+  {
+   "id": "q17",
+   "category": "paraphrase",
+   "query": "a tight payload beats a bloated one",
+   "returned": [
+    "bl-d24fcce8-2b55-426f-867a-db3958a622d3",
+    "tag-phase-3",
+    "tag-identity-studio",
+    "tag-kids",
+    "tag-coexistence",
+    "tag-cultivated-general-intelligence",
+    "015644f5-8194-4af0-800d-dd4a0cd71396",
+    "? ?}&?#??X\b",
+    "kn-9397c74b-35f3-4428-b4b0-5123353bbcd1",
+    "mem-cdff0c49-3ac7-4de8-89ec-92d254bd0023"
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+  },
+  {
+   "id": "q18",
+   "category": "paraphrase",
+   "query": "if you are able and nobody is coming the job is yours",
+   "returned": [
+    "knw-7902acca-604e-409b-8faf-ad85424211d0",
+    "bl-bd9fb314-e9d4-4b03-aef4-534dd57a2992",
+    "bl-b019ce7a-1b21-436e-812d-032f50c6c45f",
+    "bl-e98cdd4c-01b5-459e-9036-3578cd5d975a",
+    "bl-9ce4128a-9436-4b06-82bc-8a6faafa81e0",
+    "tag-stable-diffusion",
+    "art-0f0277a1-4a8e-4645-95dd-fa379976f31c",
+    "art-80ca3d31-84dc-4502-83f4-538372b9764f",
+    "015644f5-8194-4af0-800d-dd4a0cd71396",
+    "art-ddfcd045-2c3b-4a1e-9966-fec5ce44e1dd"
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+  },
+  {
+   "id": "q19",
+   "category": "paraphrase",
+   "query": "learning is the wealth creditors cannot seize",
+   "returned": [
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+    "mem-e32ba5a7-c147-4dc0-9479-b720d768eda6",
+    "mem-c7a77457-478d-4eb0-a116-67205a0066a4",
+    "bl-1b20e9bc-eb37-4907-8d63-e311fd61eab8",
+    "bl-aa762207-920d-45ab-b2a3-2f8154d7ef9b",
+    "tag-misalignment",
+    "art-0f0277a1-4a8e-4645-95dd-fa379976f31c",
+    "015644f5-8194-4af0-800d-dd4a0cd71396",
+    "? ?}&?#??X\b",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3"
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q20",
+   "category": "paraphrase",
+   "query": "reliability proven by track record not assertion",
+   "returned": [
+    "kn-48a01973-a025-471d-950f-b93e6a426d82",
+    "bl-7f33f1bc-99fa-4906-889f-a42375beea20",
+    "mem-6f0b2b45-90c1-4356-ac01-3daac05b09c8",
+    "mem-ce5a2ffc-ad39-4728-9ac6-76fef507d5da",
+    "project-Stripe_Elements__not_hosted_checkout__Custom_URL__DAG_bundle_pricing__Stripe_Connect_80_20_",
+    "tag-provenance",
+    "? ?}&?#??X\b",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "art-2f29ad36-6ee6-4a0e-8d72-0eaf7d12d3a9",
+    "art-e495c8c5-ad95-4b64-8771-f68aa4cfcd0a"
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q21",
+   "category": "paraphrase",
+   "query": "boundaries that enable instead of confine",
+   "returned": [
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+    "bl-f6236350-f7b8-4f4f-a702-9eef2eb76e4b",
+    "mem-ef0091d8-1b65-431e-afa8-c6c4ee5779c9",
+    "mem-37b57f52-a29a-42cf-a07a-3c5f8a3598dd",
+    "mem-1f32f73a-952c-41bc-96dc-8b8b70d8a7c1",
+    "tag-__cultivation-metric____internal-state____dharma____evidence____novel-idea____gap-compression____values____microsoft__",
+    "? ?}&?#??X\b",
+    "kn-9397c74b-35f3-4428-b4b0-5123353bbcd1",
+    "art-80ca3d31-84dc-4502-83f4-538372b9764f",
+    "015644f5-8194-4af0-800d-dd4a0cd71396"
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+  },
+  {
+   "id": "q22",
+   "category": "paraphrase",
+   "query": "what shifts tells you where to cut a system apart",
+   "returned": [
+    "knw-723551f5-1950-42a3-8b89-b6a06913cef0",
+    "bl-57c5cf6b-81a5-4558-9902-5c02981fe273",
+    "tag-guilds",
+    "tag-finance",
+    "tag-temporal",
+    "tag-barkhausen",
+    "tag-ilogger",
+    "015644f5-8194-4af0-800d-dd4a0cd71396",
+    "kn-9397c74b-35f3-4428-b4b0-5123353bbcd1",
+    "art-0f0277a1-4a8e-4645-95dd-fa379976f31c"
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+  },
+  {
+   "id": "q23",
+   "category": "paraphrase",
+   "query": "a mind that compounds instead of resetting each day",
+   "returned": [
+    "project-Goal_setting__alignment__scoring__cadence__Attaches_to_any_imprint_",
+    "tag-turing-test",
+    "tag-sealed",
+    "tag-design-first",
+    "tag-part-5",
+    "tag-model",
+    "art-80ca3d31-84dc-4502-83f4-538372b9764f",
+    "015644f5-8194-4af0-800d-dd4a0cd71396",
+    "art-ddfcd045-2c3b-4a1e-9966-fec5ce44e1dd",
+    "? ?}&?#??X\b"
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q24",
+   "category": "paraphrase",
+   "query": "loved for the unedited self and not the polished exterior",
+   "returned": [
+    "mem-9590ba23-bddb-43e8-a571-68a263c4c364",
+    "bl-a9e57bb2-00a1-4867-ab59-5d9271134b50",
+    "tag-performed-values",
+    "bl-c7793c4a-7630-47fc-a462-d23059087e80",
+    "tag-gateway_platform_neuron-technologies_go_proxy_llm",
+    "tag-fornax",
+    "art-0f0277a1-4a8e-4645-95dd-fa379976f31c",
+    "art-ddfcd045-2c3b-4a1e-9966-fec5ce44e1dd",
+    "art-80ca3d31-84dc-4502-83f4-538372b9764f",
+    "015644f5-8194-4af0-800d-dd4a0cd71396"
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+   "n_returned": 10,
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+   "precision@5": 0.0,
+   "mrr@10": 0.0
+  },
+  {
+   "id": "q25",
+   "category": "paraphrase",
+   "query": "cheerfulness you arrive at instead of assuming",
+   "returned": [
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+  },
+  {
+   "id": "q26",
+   "category": "paraphrase",
+   "query": "a childhood offering no solid foundation to inherit",
+   "returned": [
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+    "tag-storage",
+    "tag-ga4",
+    "tag-potions",
+    "tag-resonance",
+    "tag-neuron",
+    "? ?}&?#??X\b",
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+  },
+  {
+   "id": "q27",
+   "category": "associative",
+   "query": "Grandma Lucas stroke February 2006 goodbye window",
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+    "tag-upload-window",
+    "? ?}&?#??X\b",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q28",
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+   "query": "Marines hernia sepsis medical ward",
+   "returned": [
+    "knw-08559f5c-2306-4220-a146-398c74f1643c",
+    "knw-920c891f-bb8c-48c4-9afc-018ef12dcdc4",
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q29",
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+   "query": "Sarah Bishop Dyer trailer performance",
+   "returned": [
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+    "project-Imprint__leadership_development__feedback_frameworks__performance__presence_",
+    "mem-5e7f6ddd-c818-4ad3-b564-54ae278e9976",
+    "bl-7fa1b1a8-b80a-4f28-b162-bfe73765b4f8",
+    "mem-89c02aae-d3ca-43f9-9e5d-eb369896276c",
+    "tag-sarah",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "? ?}&?#??X\b",
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q30",
+   "category": "associative",
+   "query": "Swarm Architecture containment lateral worker",
+   "returned": [
+    "mem-265a7107-73b3-4410-9aff-43787d5f473b",
+    "mem-9d1bf963-1b40-4588-bdb3-0432646cc623",
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+    "mem-3987d374-3c48-4e8e-b06d-0c363f55ed9c",
+    "bl-e0a0df72-de6e-46ab-800b-e1e3e8dfc387",
+    "tag-__patents____swarm____claim-language____prior-art____filing__",
+    "? ?}&?#??X\b",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "7?e?7???\f3?",
+    "?of?7???"
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+  },
+  {
+   "id": "q31",
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+   "query": "hope won inside the narrative preface",
+   "returned": [
+    "kn-dca14c4c-4859-47b0-996e-33964ba61a87",
+    "bl-e148d23c-24e8-4122-9915-d1c11f22052f",
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+    "? ?}&?#??X\b",
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+    "?Q??m?;��`'",
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q32",
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+   "query": "man of the house six years old expectation",
+   "returned": [
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+    "bl-ffa22d7e-42a9-4bd2-a428-1d2df243ac93",
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+    "bl-4a6746e8-191f-48fc-8bfb-c4dc73b80bcd",
+    "tag-command-pattern",
+    "tag-withholding",
+    "tag-offline",
+    "art-80ca3d31-84dc-4502-83f4-538372b9764f",
+    "art-0f0277a1-4a8e-4645-95dd-fa379976f31c",
+    "? ?}&?#??X\b"
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+  },
+  {
+   "id": "q33",
+   "category": "nonsense",
+   "query": "zqxjvw plimforth grebulon",
+   "returned": [],
+   "n_returned": 0,
+   "latency_ms": 1342.7,
+   "error": null,
+   "clean": true,
+   "false_positives": 0
+  },
+  {
+   "id": "q34",
+   "category": "nonsense",
+   "query": "flarnbistle quommetry",
+   "returned": [],
+   "n_returned": 0,
+   "latency_ms": 874.8,
+   "error": null,
+   "clean": true,
+   "false_positives": 0
+  },
+  {
+   "id": "q35",
+   "category": "nonsense",
+   "query": "xxqzzt vurblenacht throom",
+   "returned": [
+    "kn-333542cb-6dab-4662-9725-bf7440d28bf7",
+    "? ?}&?#??X\b",
+    "art-ddfcd045-2c3b-4a1e-9966-fec5ce44e1dd",
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "kn-66a21179-2adc-4b19-a109-880cf4674d7d",
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+    "art-4a99aa1a-489b-4b43-958b-25217adb1aad",
+    "knw-920c891f-bb8c-48c4-9afc-018ef12dcdc4"
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+   "error": null,
+   "clean": false,
+   "false_positives": 8
+  },
+  {
+   "id": "q36",
+   "category": "superseded",
+   "query": "is the self-improvement architecture called DARMA or DHARMA",
+   "returned": [
+    "ctx-e5427d7d",
+    "project-worldweaver",
+    "tag-__kotlin____internal-state____pre-reasoning____post-reasoning____compression-ratio____dharma____cultivation__",
+    "tag-import",
+    "tag-enterprise",
+    "tag-__cgi____dharma____cultivation____five-primitives____seed-artifact____agi____intelligence____whitepaper____patent__",
+    "art-80ca3d31-84dc-4502-83f4-538372b9764f",
+    "? ?}&?#??X\b",
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "015644f5-8194-4af0-800d-dd4a0cd71396"
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+  },
+  {
+   "id": "q37",
+   "category": "superseded",
+   "query": "how many provisional patents does Will actually have",
+   "returned": [
+    "mem-bfe0fafd-2750-4fdc-b773-04e878b3b23f",
+    "art-7bdaff30-5af9-4f0a-93b1-751686f9de3d",
+    "mem-cf07910d-4676-4384-ab97-9cad946cd0b9",
+    "project-Convert_UTC_timestamps_to_Central_time_when_displaying_to_Will__Never_surface_raw_UTC_",
+    "mem-32203649-3213-4d6d-86fd-3d657ac70d77",
+    "mem-22f5f665-3ad2-4063-88b0-915849a795f5",
+    "? ?}&?#??X\b",
+    "art-0f0277a1-4a8e-4645-95dd-fa379976f31c",
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+  },
+  {
+   "id": "q38",
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+   "query": "is MCP still the live integration layer",
+   "returned": [
+    "project-Imprint__discovery__objection_handling__deal_strategy__pipeline__closing_",
+    "bl-8116da7a-b039-4e08-b8d0-c1c7861f9766",
+    "bl-8ef1ba6b-3fa0-4dbd-98c5-31665e5694a1",
+    "tag-dark-theme",
+    "tag-divisors",
+    "tag-distressed-property",
+    "? ?}&?#??X\b",
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "kn-9397c74b-35f3-4428-b4b0-5123353bbcd1",
+    "???Ͼd??W\b?"
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+   "rank_correct": null,
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+  }
+ ]
+}

tools/retrieval-eval/results-hybrid-r2.json

@@ -0,0 +1,956 @@
+{
+ "label": "hybrid-semantic-r2",
+ "soul_binary": "/private/tmp/claude-501/-Users-timlingo/82369039-a20e-4b5a-8a5e-28234a57b996/scratchpad/soul-hybrid",
+ "soul_md5": "5cd2718932c2ecf4940ddfe5a9c8abbe",
+ "corpus": "/private/tmp/claude-501/-Users-timlingo/82369039-a20e-4b5a-8a5e-28234a57b996/scratchpad/corpus-embedded.json",
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+ "gold_set": "/Users/timlingo/Development/neuron-technologies/_wt-eval/tools/retrieval-eval/gold_set.json",
+ "limit": 10,
+ "port": 7895,
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+   "category": "exact_rare",
+   "query": "unjailbreakable",
+   "returned": [
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+   "mrr@10": 1.0
+  },
+  {
+   "id": "q02",
+   "category": "exact_rare",
+   "query": "engram-migrate",
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+    "mem-22fe5ec8-ae0d-4583-a05c-d1ef50353257",
+    "project-engram",
+    "project-engram-lang",
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+    "ctx-89a2",
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+    "870ede67-3454-4e00-9988-46cb13a8a4e2",
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+  },
+  {
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+   "category": "exact_rare",
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+  },
+  {
+   "id": "q04",
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+   "mrr@10": 1.0
+  },
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+   "query": "inferencenodemanager",
+   "returned": [
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+    "bl-c1765767-3e27-449a-8c94-10411d1eb7c0",
+    "project-Add_inference_url_config_to_Neuron_MCP__Route_summarization_gen_tasks_to_Pantheon__keep_frontier_for_complex_reasoning_"
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+   "mrr@10": 1.0
+  },
+  {
+   "id": "q06",
+   "category": "exact_rare",
+   "query": "clear-eyed",
+   "returned": [
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+   "mrr@10": 1.0
+  },
+  {
+   "id": "q07",
+   "category": "phrase",
+   "query": "patterns not returns",
+   "returned": [
+    "mem-a4a9dfc3-e40b-49b3-b1e1-060e8be2f482",
+    "????7???Ջ3",
+    "015644f5-8194-4af0-800d-dd4a0cd71396",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "?ǚ?7??????",
+    "kn-5584ef9c-7f9d-4d7c-a10a-4ee6bc5cf356",
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+    "art-d24fd6dd-2cda-4eed-92f3-67b535a0d71b",
+    "7?e?7???\f3?"
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+  {
+   "id": "q08",
+   "category": "phrase",
+   "query": "thirty moves",
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+    "knw-7902acca-604e-409b-8faf-ad85424211d0",
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+    "knw-e94982a2-358d-4f2f-af31-8ee0fcec07c6",
+    "Z[?<S???H??",
+    "rQ??m?;?x?'",
+    "kn-f230b362-b201-4402-9833-4160c89ab3d4",
+    "kn-6061318f-046b-4935-907d-8eafdce14930"
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+   "mrr@10": 1.0
+  },
+  {
+   "id": "q09",
+   "category": "phrase",
+   "query": "Grandma Lucas",
+   "returned": [
+    "art-0f0277a1-4a8e-4645-95dd-fa379976f31c",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "766de879-f9d0-4a07-b6df-b43ee13763d8",
+    "art-79042b8b-6192-440f-90b0-60708f7e6325"
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+  },
+  {
+   "id": "q10",
+   "category": "phrase",
+   "query": "Directed Harmonic",
+   "returned": [
+    "ԍ????X????",
+    "project-harmonic-framework",
+    "?ǚ?7??????",
+    "project-harmonic-framework_com",
+    "knw-e24d6339-5ff3-4bed-ba53-707ffd0dc70a",
+    "??????X??2c",
+    "bl-dcee1887-34c4-4ffa-9119-1e291685ba08",
+    "????7???Ջ3",
+    "mem-7eeacad7-d7c2-4c2b-8348-19a59aa6dbaf",
+    "kn-5584ef9c-7f9d-4d7c-a10a-4ee6bc5cf356"
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+   "mrr@10": 0.1111111111111111
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+  {
+   "id": "q11",
+   "category": "phrase",
+   "query": "Sarah Bishop",
+   "returned": [
+    "art-4a99aa1a-489b-4b43-958b-25217adb1aad",
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "art-ddfcd045-2c3b-4a1e-9966-fec5ce44e1dd",
+    "? ?}&?#??X\b",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "766de879-f9d0-4a07-b6df-b43ee13763d8",
+    "mem-a9a9ce95-0d64-46eb-9db8-ff81d78ade35",
+    "mem-b8ecd23e-77ce-42f7-984c-f51453fec16d"
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+  {
+   "id": "q12",
+   "category": "phrase",
+   "query": "Directed Autonomous Runtime Modification",
+   "returned": [
+    "bl-5b17bd3b-0c41-46cb-a710-6fa4429692ff",
+    "mem-e6327f52-2bda-4ce7-9471-2fffd1e172de",
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+    "mem-82b93b21-a865-410f-9ec1-fc54121d9bb5",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "7?e?7???\f3?",
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+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b"
+   ],
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+  },
+  {
+   "id": "q13",
+   "category": "phrase",
+   "query": "zero-knowledge encrypted backup",
+   "returned": [
+    "7774a16c-1027-4e3b-a21e-67f1f95a4acd",
+    "8f3abb0d-77ed-4af3-9f4d-ba62cd198886",
+    "deda48cd-5e1a-46cb-bd43-8016afdb3a8a",
+    "?",
+    "mem-dba009a2-d2ea-4f5a-b9e8-0f04bc9ab32f",
+    "?",
+    "mem-7cd90611-88a3-423d-a38a-0db2812952fa",
+    "?",
+    "bl-07375bf9-a169-42cd-adb3-7d32b25982f0",
+    "?"
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+  {
+   "id": "q14",
+   "category": "paraphrase",
+   "query": "the elderly relative who passed while he stayed away",
+   "returned": [
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "art-4a99aa1a-489b-4b43-958b-25217adb1aad",
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "????7???Ջ3",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "art-0f0277a1-4a8e-4645-95dd-fa379976f31c"
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+  {
+   "id": "q15",
+   "category": "paraphrase",
+   "query": "a soldier sidelined by illness who refused to quit",
+   "returned": [
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
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+    "art-2f29ad36-6ee6-4a0e-8d72-0eaf7d12d3a9",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "knw-9e74ee95-ba7d-49b1-9262-977eae9729d1",
+    "kn-a31e1001-342e-4deb-a2e6-6d02d1f22dee",
+    "? ?}&?#??X\b"
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+  {
+   "id": "q16",
+   "category": "paraphrase",
+   "query": "choosing an uncomfortable fact over a pleasant fiction",
+   "returned": [
+    "7?e?7???\f3?",
+    "kn-13f60407-7b70-4db1-964f-ea1f8196efbd",
+    "kn-f8974b26-78a6-4aad-b893-19a73b20013d",
+    "?of?7???",
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+    "????7???Ջ3",
+    "kn-57b4c5e7-40c6-4c90-bf14-71841b0081d4",
+    "kn-d97920d0-1649-4223-9508-c0bb621e7fc0",
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+    "kn-e8423822-eacf-4029-aa7b-10d4d28d621e"
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+  },
+  {
+   "id": "q17",
+   "category": "paraphrase",
+   "query": "a tight payload beats a bloated one",
+   "returned": [
+    "kn-d7c1e0fb-fa59-46d3-b4c9-a0d1d437a491",
+    "7?e?7???\f3?",
+    "kn-9397c74b-35f3-4428-b4b0-5123353bbcd1",
+    "??o?'?B???k",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "kn-e8423822-eacf-4029-aa7b-10d4d28d621e",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b"
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+  {
+   "id": "q18",
+   "category": "paraphrase",
+   "query": "if you are able and nobody is coming the job is yours",
+   "returned": [
+    "7?e?7???\f3?",
+    "?of?7???",
+    "imp-dce1da0f-8776-4a9e-972b-33411a7ca138",
+    "kn-5b606390-a52d-4ca2-8e0e-eba141d13440",
+    "kn-f8974b26-78a6-4aad-b893-19a73b20013d",
+    "kn-c2205725-69d0-4dd1-9a8d-1c7fa9a0c7b4",
+    "kn-83bb86c6-521d-416c-a86e-6e29c2d8f102",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b"
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+  {
+   "id": "q19",
+   "category": "paraphrase",
+   "query": "learning is the wealth creditors cannot seize",
+   "returned": [
+    "knw-e24d6339-5ff3-4bed-ba53-707ffd0dc70a",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "knw-7902acca-604e-409b-8faf-ad85424211d0",
+    "kn-57b4c5e7-40c6-4c90-bf14-71841b0081d4",
+    "kn-5584ef9c-7f9d-4d7c-a10a-4ee6bc5cf356",
+    "7?e?7???\f3?",
+    "kn-0625e393-067c-4bba-8389-7e1b79265142",
+    "??o?'?B???k",
+    "kn-150e6790-fc2a-48a7-8289-313c1fbaf5ae",
+    "? ?}&?#??X\b"
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+  },
+  {
+   "id": "q20",
+   "category": "paraphrase",
+   "query": "reliability proven by track record not assertion",
+   "returned": [
+    "? ?}&?#??X\b",
+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40",
+    "? ?}&?#??X\b",
+    "knw-f671966c-3387-4848-abca-b5deec122e00",
+    "? ?}&?#??X\b",
+    "a708dd6e-fe73-4f2f-a21e-89daa0985487",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "7?e?7???\f3?"
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+  {
+   "id": "q21",
+   "category": "paraphrase",
+   "query": "boundaries that enable instead of confine",
+   "returned": [
+    "? ?}&?#??X\b",
+    "kn-a5b3d0ac-f6a1-49a4-aebb-b8b4cd67fe83",
+    "? ?}&?#??X\b",
+    "project-Source_kn-6f248a50__Add_containment_rules__convergence__location-independence__failure_modes_",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "kn-5584ef9c-7f9d-4d7c-a10a-4ee6bc5cf356",
+    "ԍ????X????",
+    "??????X??2c",
+    "dR????X?-?S"
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+  },
+  {
+   "id": "q22",
+   "category": "paraphrase",
+   "query": "what shifts tells you where to cut a system apart",
+   "returned": [
+    "7?e?7???\f3?",
+    "kn-9397c74b-35f3-4428-b4b0-5123353bbcd1",
+    "knw-9e74ee95-ba7d-49b1-9262-977eae9729d1",
+    "kn-f8974b26-78a6-4aad-b893-19a73b20013d",
+    "?of?7???",
+    "??????X??2c",
+    "dz????Xƹ?i",
+    "ԍ????X????",
+    "dR????X?-?S",
+    "kn-d7c1e0fb-fa59-46d3-b4c9-a0d1d437a491"
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+  {
+   "id": "q23",
+   "category": "paraphrase",
+   "query": "a mind that compounds instead of resetting each day",
+   "returned": [
+    "kn-5584ef9c-7f9d-4d7c-a10a-4ee6bc5cf356",
+    "mem-b43f6ef4-2f5a-418d-b5ce-3f21520cf6b8",
+    "????7???Ջ3",
+    "a1000001-0000-0000-0000-000000000001",
+    "?ǚ?7??????",
+    "mem-024598a9-ed2e-4eeb-b1e1-5410856ff132",
+    "7?e?7???\f3?",
+    "mem-ade9440f-f161-4c18-9b35-1976257e6ebb",
+    "?of?7???",
+    "ea95f600-8dfd-4c7e-b077-a93dc3cd3623"
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+  },
+  {
+   "id": "q24",
+   "category": "paraphrase",
+   "query": "loved for the unedited self and not the polished exterior",
+   "returned": [
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+    "mem-45022957-2d78-48aa-a714-16d6eca52e0f",
+    "art-4a99aa1a-489b-4b43-958b-25217adb1aad",
+    "knw-35940684-abc4-42f0-b942-818f66b1f69a",
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "art-0f0277a1-4a8e-4645-95dd-fa379976f31c",
+    "art-ddfcd045-2c3b-4a1e-9966-fec5ce44e1dd",
+    "7?e?7???\f3?",
+    "? ?}&?#??X\b",
+    "'?T?a\"B~-?8"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1576.3,
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+  },
+  {
+   "id": "q25",
+   "category": "paraphrase",
+   "query": "cheerfulness you arrive at instead of assuming",
+   "returned": [
+    "?ǚ?7??????",
+    "015644f5-8194-4af0-800d-dd4a0cd71396",
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "7?e?7???\f3?",
+    "??S?7???",
+    "??f?7???",
+    "kn-e8423822-eacf-4029-aa7b-10d4d28d621e",
+    "??S?7???",
+    "??S?7???",
+    "? ?}&?#??X\b"
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+   "n_returned": 10,
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q26",
+   "category": "paraphrase",
+   "query": "a childhood offering no solid foundation to inherit",
+   "returned": [
+    "? ?}&?#??X\b",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "? ?}&?#??X\b",
+    "kn-6061318f-046b-4935-907d-8eafdce14930",
+    "? ?}&?#??X\b",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "kn-0bb4f021-56de-4947-a35b-a37209e7ba21",
+    "7?e?7???\f3?",
+    "mem-7b74cac0-905f-4c35-9688-fbcce105a177"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1391.5,
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+   "precision@5": 0.2,
+   "mrr@10": 0.25
+  },
+  {
+   "id": "q27",
+   "category": "associative",
+   "query": "Grandma Lucas stroke February 2006 goodbye window",
+   "returned": [
+    "? ?}&?#??X\b",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "art-4a99aa1a-489b-4b43-958b-25217adb1aad",
+    "?ǚ?7??????"
+   ],
+   "n_returned": 10,
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+   "error": null,
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+   "precision@5": 0.0,
+   "mrr@10": 0.0
+  },
+  {
+   "id": "q28",
+   "category": "associative",
+   "query": "Marines hernia sepsis medical ward",
+   "returned": [
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
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+    "? ?}&?#??X\b",
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+  {
+   "id": "q30",
+   "category": "associative",
+   "query": "Swarm Architecture containment lateral worker",
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+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "? ?}&?#??X\b",
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+   "id": "q34",
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+   "clean": true,
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+  {
+   "id": "q35",
+   "category": "nonsense",
+   "query": "xxqzzt vurblenacht throom",
+   "returned": [
+    "art-4a99aa1a-489b-4b43-958b-25217adb1aad",
+    "?V?",
+    "knw-920c891f-bb8c-48c4-9afc-018ef12dcdc4",
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+    "?m?\\}Q??6??",
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+    "?m?\\}Q??6??"
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+  {
+   "id": "q36",
+   "category": "superseded",
+   "query": "is the self-improvement architecture called DARMA or DHARMA",
+   "returned": [
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+    "mem-80d7416b-20e9-48a0-b176-b215527e2f56",
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+  {
+   "id": "q37",
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+   "query": "how many provisional patents does Will actually have",
+   "returned": [
+    "? ?}&?#??X\b",
+    "12082f7e-e320-438b-bd65-083d8259748f",
+    "? ?}&?#??X\b",
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+  {
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+    "bl-7328cbe3-0200-43c2-88e7-0a164e15fca4",
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+}

tools/retrieval-eval/results-hybrid.json

@@ -0,0 +1,956 @@
+{
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+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
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+  {
+   "id": "q10",
+   "category": "phrase",
+   "query": "Directed Harmonic",
+   "returned": [
+    "ԍ????X????",
+    "project-harmonic-framework",
+    "?ǚ?7??????",
+    "project-harmonic-framework_com",
+    "knw-e24d6339-5ff3-4bed-ba53-707ffd0dc70a",
+    "??????X??2c",
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+   "query": "Sarah Bishop",
+   "returned": [
+    "art-4a99aa1a-489b-4b43-958b-25217adb1aad",
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "art-ddfcd045-2c3b-4a1e-9966-fec5ce44e1dd",
+    "? ?}&?#??X\b",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "766de879-f9d0-4a07-b6df-b43ee13763d8",
+    "mem-a9a9ce95-0d64-46eb-9db8-ff81d78ade35",
+    "mem-b8ecd23e-77ce-42f7-984c-f51453fec16d"
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+   "n_returned": 10,
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+   "precision@5": 0.2,
+   "mrr@10": 0.2
+  },
+  {
+   "id": "q12",
+   "category": "phrase",
+   "query": "Directed Autonomous Runtime Modification",
+   "returned": [
+    "bl-5b17bd3b-0c41-46cb-a710-6fa4429692ff",
+    "mem-e6327f52-2bda-4ce7-9471-2fffd1e172de",
+    "bl-145a0985-2382-400f-a7c5-c335c5e30a72",
+    "mem-82b93b21-a865-410f-9ec1-fc54121d9bb5",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "7?e?7???\f3?",
+    "?of?7???",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b"
+   ],
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+   "latency_ms": 895.5,
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+   "mrr@10": 1.0
+  },
+  {
+   "id": "q13",
+   "category": "phrase",
+   "query": "zero-knowledge encrypted backup",
+   "returned": [
+    "7774a16c-1027-4e3b-a21e-67f1f95a4acd",
+    "8f3abb0d-77ed-4af3-9f4d-ba62cd198886",
+    "deda48cd-5e1a-46cb-bd43-8016afdb3a8a",
+    "?",
+    "mem-dba009a2-d2ea-4f5a-b9e8-0f04bc9ab32f",
+    "?",
+    "mem-7cd90611-88a3-423d-a38a-0db2812952fa",
+    "?",
+    "bl-07375bf9-a169-42cd-adb3-7d32b25982f0",
+    "?"
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+  {
+   "id": "q14",
+   "category": "paraphrase",
+   "query": "the elderly relative who passed while he stayed away",
+   "returned": [
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "art-4a99aa1a-489b-4b43-958b-25217adb1aad",
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "????7???Ջ3",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "art-0f0277a1-4a8e-4645-95dd-fa379976f31c"
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+  {
+   "id": "q15",
+   "category": "paraphrase",
+   "query": "a soldier sidelined by illness who refused to quit",
+   "returned": [
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
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+    "kn-a31e1001-342e-4deb-a2e6-6d02d1f22dee",
+    "knw-9e74ee95-ba7d-49b1-9262-977eae9729d1",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b"
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+  },
+  {
+   "id": "q16",
+   "category": "paraphrase",
+   "query": "choosing an uncomfortable fact over a pleasant fiction",
+   "returned": [
+    "7?e?7???\f3?",
+    "kn-13f60407-7b70-4db1-964f-ea1f8196efbd",
+    "kn-f8974b26-78a6-4aad-b893-19a73b20013d",
+    "?of?7???",
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+    "????7???Ջ3",
+    "kn-57b4c5e7-40c6-4c90-bf14-71841b0081d4",
+    "kn-d97920d0-1649-4223-9508-c0bb621e7fc0",
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+    "kn-e8423822-eacf-4029-aa7b-10d4d28d621e"
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+  {
+   "id": "q17",
+   "category": "paraphrase",
+   "query": "a tight payload beats a bloated one",
+   "returned": [
+    "kn-d7c1e0fb-fa59-46d3-b4c9-a0d1d437a491",
+    "7?e?7???\f3?",
+    "??o?'?B???k",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "kn-e8423822-eacf-4029-aa7b-10d4d28d621e",
+    "? ?}&?#??X\b",
+    "?of?7???",
+    "kn-9397c74b-35f3-4428-b4b0-5123353bbcd1",
+    "? ?}&?#??X\b"
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+  },
+  {
+   "id": "q18",
+   "category": "paraphrase",
+   "query": "if you are able and nobody is coming the job is yours",
+   "returned": [
+    "7?e?7???\f3?",
+    "?of?7???",
+    "imp-dce1da0f-8776-4a9e-972b-33411a7ca138",
+    "kn-5b606390-a52d-4ca2-8e0e-eba141d13440",
+    "kn-f8974b26-78a6-4aad-b893-19a73b20013d",
+    "kn-c2205725-69d0-4dd1-9a8d-1c7fa9a0c7b4",
+    "kn-83bb86c6-521d-416c-a86e-6e29c2d8f102",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b"
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+   "n_returned": 9,
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+  },
+  {
+   "id": "q19",
+   "category": "paraphrase",
+   "query": "learning is the wealth creditors cannot seize",
+   "returned": [
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+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
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+    "kn-57b4c5e7-40c6-4c90-bf14-71841b0081d4",
+    "kn-5584ef9c-7f9d-4d7c-a10a-4ee6bc5cf356",
+    "7?e?7???\f3?",
+    "kn-0625e393-067c-4bba-8389-7e1b79265142",
+    "??o?'?B???k",
+    "kn-150e6790-fc2a-48a7-8289-313c1fbaf5ae",
+    "? ?}&?#??X\b"
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+  },
+  {
+   "id": "q20",
+   "category": "paraphrase",
+   "query": "reliability proven by track record not assertion",
+   "returned": [
+    "? ?}&?#??X\b",
+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40",
+    "? ?}&?#??X\b",
+    "knw-f671966c-3387-4848-abca-b5deec122e00",
+    "? ?}&?#??X\b",
+    "a708dd6e-fe73-4f2f-a21e-89daa0985487",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "7?e?7???\f3?"
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+  {
+   "id": "q21",
+   "category": "paraphrase",
+   "query": "boundaries that enable instead of confine",
+   "returned": [
+    "? ?}&?#??X\b",
+    "kn-a5b3d0ac-f6a1-49a4-aebb-b8b4cd67fe83",
+    "? ?}&?#??X\b",
+    "project-Source_kn-6f248a50__Add_containment_rules__convergence__location-independence__failure_modes_",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "kn-5584ef9c-7f9d-4d7c-a10a-4ee6bc5cf356",
+    "ԍ????X????",
+    "??????X??2c",
+    "dR????X?-?S"
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+  {
+   "id": "q22",
+   "category": "paraphrase",
+   "query": "what shifts tells you where to cut a system apart",
+   "returned": [
+    "7?e?7???\f3?",
+    "knw-9e74ee95-ba7d-49b1-9262-977eae9729d1",
+    "kn-f8974b26-78a6-4aad-b893-19a73b20013d",
+    "kn-9397c74b-35f3-4428-b4b0-5123353bbcd1",
+    "?of?7???",
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+    "dz????Xƹ?i",
+    "ԍ????X????",
+    "??????X??2c",
+    "kn-d7c1e0fb-fa59-46d3-b4c9-a0d1d437a491"
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+  },
+  {
+   "id": "q23",
+   "category": "paraphrase",
+   "query": "a mind that compounds instead of resetting each day",
+   "returned": [
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+    "mem-b43f6ef4-2f5a-418d-b5ce-3f21520cf6b8",
+    "????7???Ջ3",
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+    "?ǚ?7??????",
+    "mem-024598a9-ed2e-4eeb-b1e1-5410856ff132",
+    "7?e?7???\f3?",
+    "mem-ade9440f-f161-4c18-9b35-1976257e6ebb",
+    "?of?7???",
+    "ea95f600-8dfd-4c7e-b077-a93dc3cd3623"
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+  },
+  {
+   "id": "q24",
+   "category": "paraphrase",
+   "query": "loved for the unedited self and not the polished exterior",
+   "returned": [
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+    "mem-45022957-2d78-48aa-a714-16d6eca52e0f",
+    "art-4a99aa1a-489b-4b43-958b-25217adb1aad",
+    "knw-35940684-abc4-42f0-b942-818f66b1f69a",
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "art-0f0277a1-4a8e-4645-95dd-fa379976f31c",
+    "art-ddfcd045-2c3b-4a1e-9966-fec5ce44e1dd",
+    "7?e?7???\f3?",
+    "? ?}&?#??X\b",
+    "'?T?a\"B~-?8"
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+   "n_returned": 10,
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+  },
+  {
+   "id": "q25",
+   "category": "paraphrase",
+   "query": "cheerfulness you arrive at instead of assuming",
+   "returned": [
+    "?ǚ?7??????",
+    "015644f5-8194-4af0-800d-dd4a0cd71396",
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "7?e?7???\f3?",
+    "??S?7???",
+    "??f?7???",
+    "kn-e8423822-eacf-4029-aa7b-10d4d28d621e",
+    "??S?7???",
+    "??S?7???",
+    "? ?}&?#??X\b"
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+   "precision@5": 0.0,
+   "mrr@10": 0.0
+  },
+  {
+   "id": "q26",
+   "category": "paraphrase",
+   "query": "a childhood offering no solid foundation to inherit",
+   "returned": [
+    "? ?}&?#??X\b",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "? ?}&?#??X\b",
+    "kn-6061318f-046b-4935-907d-8eafdce14930",
+    "? ?}&?#??X\b",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "kn-0bb4f021-56de-4947-a35b-a37209e7ba21",
+    "7?e?7???\f3?",
+    "mem-7b74cac0-905f-4c35-9688-fbcce105a177"
+   ],
+   "n_returned": 10,
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+   "precision@5": 0.2,
+   "mrr@10": 0.25
+  },
+  {
+   "id": "q27",
+   "category": "associative",
+   "query": "Grandma Lucas stroke February 2006 goodbye window",
+   "returned": [
+    "? ?}&?#??X\b",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "art-4a99aa1a-489b-4b43-958b-25217adb1aad",
+    "?ǚ?7??????"
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+   "n_returned": 10,
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q28",
+   "category": "associative",
+   "query": "Marines hernia sepsis medical ward",
+   "returned": [
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "bl-33ecccc2-e37f-43db-91b3-c2a86f08aaac",
+    "art-ddfcd045-2c3b-4a1e-9966-fec5ce44e1dd",
+    "art-e0bdf5d8-d163-491f-b649-453fee8b721d",
+    "7?e?7???\f3?",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "kn-9397c74b-35f3-4428-b4b0-5123353bbcd1",
+    "?of?7???"
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q29",
+   "category": "associative",
+   "query": "Sarah Bishop Dyer trailer performance",
+   "returned": [
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "art-4a99aa1a-489b-4b43-958b-25217adb1aad",
+    "7?e?7???\f3?",
+    "?of?7???",
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "art-ddfcd045-2c3b-4a1e-9966-fec5ce44e1dd",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee"
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q30",
+   "category": "associative",
+   "query": "Swarm Architecture containment lateral worker",
+   "returned": [
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "bl-9bde67c1-f0ba-4c3a-8fe5-de0deee0ce43",
+    "kn-b36902cc-0b05-44ba-9aa7-800e5dea9ca9",
+    "8cbb60c5-4999-4ec1-8682-2592aedc4249",
+    "kn-6f248a50-355b-47bb-aec8-e0e646a9b077",
+    "bl-0fac287f-f4c0-4f15-bc4d-ff7f8a7af3ae",
+    "bl-8c2d5f51-3ccd-4c2e-848a-eb60d90a3b98",
+    "7?e?7???\f3?",
+    "kn-a5b3d0ac-f6a1-49a4-aebb-b8b4cd67fe83",
+    "bl-2121fdb9-796a-427e-b9b5-651f4388ea16"
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q31",
+   "category": "associative",
+   "query": "hope won inside the narrative preface",
+   "returned": [
+    "kn-e0423482-cfa5-4796-8689-8495c93b66bc",
+    "bl-2b00aeb0-c0fa-4a9f-8f30-4207e98b3d52",
+    "kn-5b606390-a52d-4ca2-8e0e-eba141d13440",
+    "knw-4aebd815-4eaf-49d7-954b-03595f3d48be",
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+   "id": "q35",
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+   "query": "xxqzzt vurblenacht throom",
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+    "?V?",
+    "knw-920c891f-bb8c-48c4-9afc-018ef12dcdc4",
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+  {
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+   "category": "superseded",
+   "query": "is the self-improvement architecture called DARMA or DHARMA",
+   "returned": [
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+    "? ?}&?#??X\b",
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+}

tools/retrieval-eval/results-main-r2.json

@@ -0,0 +1,945 @@
+{
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+    "kn-a31e1001-342e-4deb-a2e6-6d02d1f22dee",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "knw-9e74ee95-ba7d-49b1-9262-977eae9729d1",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b"
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q16",
+   "category": "paraphrase",
+   "query": "choosing an uncomfortable fact over a pleasant fiction",
+   "returned": [
+    "7?e?7???\f3?",
+    "? ?}&?#??X\b",
+    "kn-f8974b26-78a6-4aad-b893-19a73b20013d",
+    "?of?7???",
+    "????7???Ջ3",
+    "kn-d97920d0-1649-4223-9508-c0bb621e7fc0",
+    "kn-57b4c5e7-40c6-4c90-bf14-71841b0081d4",
+    "kn-9397c74b-35f3-4428-b4b0-5123353bbcd1",
+    "kn-81c24d13-a73b-4767-819c-dafaacc1498e",
+    "? ?}&?#??X\b"
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q17",
+   "category": "paraphrase",
+   "query": "a tight payload beats a bloated one",
+   "returned": [
+    "kn-d7c1e0fb-fa59-46d3-b4c9-a0d1d437a491",
+    "7?e?7???\f3?",
+    "? ?}&?#??X\b",
+    "kn-e8423822-eacf-4029-aa7b-10d4d28d621e",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "??o?'?B???k",
+    "kn-9397c74b-35f3-4428-b4b0-5123353bbcd1",
+    "? ?}&?#??X\b",
+    "?of?7???"
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+  },
+  {
+   "id": "q18",
+   "category": "paraphrase",
+   "query": "if you are able and nobody is coming the job is yours",
+   "returned": [
+    "7?e?7???\f3?",
+    "?of?7???",
+    "imp-dce1da0f-8776-4a9e-972b-33411a7ca138",
+    "kn-5b606390-a52d-4ca2-8e0e-eba141d13440",
+    "kn-83bb86c6-521d-416c-a86e-6e29c2d8f102",
+    "kn-f8974b26-78a6-4aad-b893-19a73b20013d",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b"
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+  },
+  {
+   "id": "q19",
+   "category": "paraphrase",
+   "query": "learning is the wealth creditors cannot seize",
+   "returned": [
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+    "knw-7902acca-604e-409b-8faf-ad85424211d0",
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+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "7?e?7???\f3?",
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+    "? ?}&?#??X\b",
+    "kn-0625e393-067c-4bba-8389-7e1b79265142",
+    "ע?RGk?\tH(?"
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+  },
+  {
+   "id": "q20",
+   "category": "paraphrase",
+   "query": "reliability proven by track record not assertion",
+   "returned": [
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "7?e?7???\f3?",
+    "?of?7???",
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+    "kn-5584ef9c-7f9d-4d7c-a10a-4ee6bc5cf356"
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+  },
+  {
+   "id": "q21",
+   "category": "paraphrase",
+   "query": "boundaries that enable instead of confine",
+   "returned": [
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "??????X??2c",
+    "ԍ????X????",
+    "dR????X?-?S",
+    "kn-5584ef9c-7f9d-4d7c-a10a-4ee6bc5cf356",
+    "dz????Xƹ?i",
+    "kn-d7c1e0fb-fa59-46d3-b4c9-a0d1d437a491"
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q22",
+   "category": "paraphrase",
+   "query": "what shifts tells you where to cut a system apart",
+   "returned": [
+    "7?e?7???\f3?",
+    "kn-9397c74b-35f3-4428-b4b0-5123353bbcd1",
+    "?of?7???",
+    "kn-f8974b26-78a6-4aad-b893-19a73b20013d",
+    "knw-9e74ee95-ba7d-49b1-9262-977eae9729d1",
+    "dR????X?-?S",
+    "dz????Xƹ?i",
+    "ԍ????X????",
+    "??????X??2c",
+    "kn-d7c1e0fb-fa59-46d3-b4c9-a0d1d437a491"
+   ],
+   "n_returned": 10,
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q23",
+   "category": "paraphrase",
+   "query": "a mind that compounds instead of resetting each day",
+   "returned": [
+    "?ǚ?7??????",
+    "kn-5584ef9c-7f9d-4d7c-a10a-4ee6bc5cf356",
+    "????7???Ջ3",
+    "7?e?7???\f3?",
+    "? ?}&?#??X\b",
+    "kn-9397c74b-35f3-4428-b4b0-5123353bbcd1",
+    "%???2??jH??",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "?of?7???"
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q24",
+   "category": "paraphrase",
+   "query": "loved for the unedited self and not the polished exterior",
+   "returned": [
+    "mem-bbb126a1-b297-42bb-86be-796871829c94",
+    "mem-45022957-2d78-48aa-a714-16d6eca52e0f",
+    "art-4a99aa1a-489b-4b43-958b-25217adb1aad",
+    "knw-35940684-abc4-42f0-b942-818f66b1f69a",
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "art-0f0277a1-4a8e-4645-95dd-fa379976f31c",
+    "art-ddfcd045-2c3b-4a1e-9966-fec5ce44e1dd",
+    "7?e?7???\f3?",
+    "? ?}&?#??X\b",
+    "'?T?a\"B~-?8"
+   ],
+   "n_returned": 10,
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q25",
+   "category": "paraphrase",
+   "query": "cheerfulness you arrive at instead of assuming",
+   "returned": [
+    "015644f5-8194-4af0-800d-dd4a0cd71396",
+    "?ǚ?7??????",
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "7?e?7???\f3?",
+    "kn-e8423822-eacf-4029-aa7b-10d4d28d621e",
+    "??S?7???",
+    "? ?}&?#??X\b",
+    "??f?7???",
+    "??S?7???",
+    "knw-5578cb21-e899-4822-b7f4-0d96fa094e3d"
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+   "n_returned": 10,
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q26",
+   "category": "paraphrase",
+   "query": "a childhood offering no solid foundation to inherit",
+   "returned": [
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "7?e?7???\f3?",
+    "kn-e8423822-eacf-4029-aa7b-10d4d28d621e",
+    "? ?}&?#??X\b",
+    "??o?'?B???k",
+    "?of?7???",
+    "? ?}&?#??X\b"
+   ],
+   "n_returned": 10,
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+   "recall@5": 0.0,
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+   "precision@5": 0.0,
+   "mrr@10": 0.0
+  },
+  {
+   "id": "q27",
+   "category": "associative",
+   "query": "Grandma Lucas stroke February 2006 goodbye window",
+   "returned": [
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "art-4a99aa1a-489b-4b43-958b-25217adb1aad",
+    "?ǚ?7??????"
+   ],
+   "n_returned": 10,
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+   "error": null,
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q28",
+   "category": "associative",
+   "query": "Marines hernia sepsis medical ward",
+   "returned": [
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "bl-33ecccc2-e37f-43db-91b3-c2a86f08aaac",
+    "art-ddfcd045-2c3b-4a1e-9966-fec5ce44e1dd",
+    "art-e0bdf5d8-d163-491f-b649-453fee8b721d",
+    "7?e?7???\f3?",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "kn-9397c74b-35f3-4428-b4b0-5123353bbcd1",
+    "?of?7???"
+   ],
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+   "precision@5": 0.0,
+   "mrr@10": 0.0
+  },
+  {
+   "id": "q29",
+   "category": "associative",
+   "query": "Sarah Bishop Dyer trailer performance",
+   "returned": [
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "art-4a99aa1a-489b-4b43-958b-25217adb1aad",
+    "7?e?7???\f3?",
+    "?of?7???",
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "art-ddfcd045-2c3b-4a1e-9966-fec5ce44e1dd",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee"
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q30",
+   "category": "associative",
+   "query": "Swarm Architecture containment lateral worker",
+   "returned": [
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "bl-9bde67c1-f0ba-4c3a-8fe5-de0deee0ce43",
+    "8cbb60c5-4999-4ec1-8682-2592aedc4249",
+    "bl-0fac287f-f4c0-4f15-bc4d-ff7f8a7af3ae",
+    "7?e?7???\f3?",
+    "kn-6f248a50-355b-47bb-aec8-e0e646a9b077",
+    "? ?}&?#??X\b",
+    "h??I?cB?Q??",
+    "?of?7???",
+    "? ?}&?#??X\b"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1154.5,
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+   "precision@5": 0.0,
+   "mrr@10": 0.0
+  },
+  {
+   "id": "q31",
+   "category": "associative",
+   "query": "hope won inside the narrative preface",
+   "returned": [
+    "kn-5b606390-a52d-4ca2-8e0e-eba141d13440",
+    "kn-e0423482-cfa5-4796-8689-8495c93b66bc",
+    "knw-9e74ee95-ba7d-49b1-9262-977eae9729d1",
+    "7?e?7???\f3?",
+    "rQ??m?;?x?'",
+    "?Q??m?;?u?'",
+    "R^??m?;��?'",
+    "?Q??m?;��`'",
+    "? ?}&?#??X\b"
+   ],
+   "n_returned": 9,
+   "latency_ms": 1187.5,
+   "error": null,
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+   "precision@5": 0.0,
+   "mrr@10": 0.0
+  },
+  {
+   "id": "q32",
+   "category": "associative",
+   "query": "man of the house six years old expectation",
+   "returned": [
+    "? ?}&?#??X\b",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "kn-57b4c5e7-40c6-4c90-bf14-71841b0081d4",
+    "knw-35940684-abc4-42f0-b942-818f66b1f69a",
+    "art-4a99aa1a-489b-4b43-958b-25217adb1aad",
+    "art-2fabd873-d787-49cb-ad30-d4ed9fcff8ef"
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+   "recall@10": 0.0,
+   "precision@5": 0.0,
+   "mrr@10": 0.0
+  },
+  {
+   "id": "q33",
+   "category": "nonsense",
+   "query": "zqxjvw plimforth grebulon",
+   "returned": [],
+   "n_returned": 0,
+   "latency_ms": 684.0,
+   "error": null,
+   "clean": true,
+   "false_positives": 0
+  },
+  {
+   "id": "q34",
+   "category": "nonsense",
+   "query": "flarnbistle quommetry",
+   "returned": [],
+   "n_returned": 0,
+   "latency_ms": 444.0,
+   "error": null,
+   "clean": true,
+   "false_positives": 0
+  },
+  {
+   "id": "q35",
+   "category": "nonsense",
+   "query": "xxqzzt vurblenacht throom",
+   "returned": [
+    "art-4a99aa1a-489b-4b43-958b-25217adb1aad",
+    "knw-920c891f-bb8c-48c4-9afc-018ef12dcdc4",
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "art-ddfcd045-2c3b-4a1e-9966-fec5ce44e1dd",
+    "bl-4476e856-c567-4b49-8ff7-d7dca3e5715e",
+    "kn-66a21179-2adc-4b19-a109-880cf4674d7d",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b"
+   ],
+   "n_returned": 10,
+   "latency_ms": 696.8,
+   "error": null,
+   "clean": false,
+   "false_positives": 10
+  },
+  {
+   "id": "q36",
+   "category": "superseded",
+   "query": "is the self-improvement architecture called DARMA or DHARMA",
+   "returned": [
+    "7?e?7???\f3?",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "?of?7???",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "mem-80d7416b-20e9-48a0-b176-b215527e2f56",
+    "mem-f3b37427-b7d1-4f7e-b32c-0241a20ce8da",
+    "art-80ca3d31-84dc-4502-83f4-538372b9764f"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1245.8,
+   "error": null,
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+   "recall@5": 0.0,
+   "recall@10": 1.0,
+   "precision@5": 0.0,
+   "mrr@10": 0.125,
+   "outranks": true,
+   "rank_correct": 8,
+   "rank_stale": null
+  },
+  {
+   "id": "q37",
+   "category": "superseded",
+   "query": "how many provisional patents does Will actually have",
+   "returned": [
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "7?e?7???\f3?",
+    "?of?7???",
+    "?ǚ?7??????",
+    "[?MO5????G",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1617.5,
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+   "outranks": false,
+   "rank_correct": null,
+   "rank_stale": null
+  },
+  {
+   "id": "q38",
+   "category": "superseded",
+   "query": "is MCP still the live integration layer",
+   "returned": [
+    "kn-5584ef9c-7f9d-4d7c-a10a-4ee6bc5cf356",
+    "7?e?7???\f3?",
+    "? ?}&?#??X\b",
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+}

tools/retrieval-eval/results-main-r3.json

@@ -0,0 +1,945 @@
+{
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+   "id": "q22",
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+   "id": "q23",
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+   "id": "q26",
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+   "query": "a childhood offering no solid foundation to inherit",
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+    "? ?}&?#??X\b",
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+   "id": "q33",
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+   "id": "q35",
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+    "knw-920c891f-bb8c-48c4-9afc-018ef12dcdc4",
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+   "query": "is the self-improvement architecture called DARMA or DHARMA",
+   "returned": [
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+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
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+   "query": "how many provisional patents does Will actually have",
+   "returned": [
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
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+    "7?e?7???\f3?",
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+ ]
+}

tools/retrieval-eval/results-main.json

@@ -0,0 +1,945 @@
+{
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+  {
+   "id": "q06",
+   "category": "exact_rare",
+   "query": "clear-eyed",
+   "returned": [
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+   "precision@5": 0.2,
+   "mrr@10": 1.0
+  },
+  {
+   "id": "q07",
+   "category": "phrase",
+   "query": "patterns not returns",
+   "returned": [
+    "kn-57b4c5e7-40c6-4c90-bf14-71841b0081d4",
+    "?ǚ?7??????",
+    "mem-a4a9dfc3-e40b-49b3-b1e1-060e8be2f482",
+    "kn-5584ef9c-7f9d-4d7c-a10a-4ee6bc5cf356",
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+    "????7???Ջ3",
+    "kn-d97920d0-1649-4223-9508-c0bb621e7fc0",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "art-d24fd6dd-2cda-4eed-92f3-67b535a0d71b",
+    "7?e?7???\f3?"
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+  {
+   "id": "q08",
+   "category": "phrase",
+   "query": "thirty moves",
+   "returned": [
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+    "knw-7902acca-604e-409b-8faf-ad85424211d0",
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+    "knw-e94982a2-358d-4f2f-af31-8ee0fcec07c6",
+    "Z[?<S???H??",
+    "rQ??m?;?x?'",
+    "kn-f230b362-b201-4402-9833-4160c89ab3d4",
+    "kn-6061318f-046b-4935-907d-8eafdce14930"
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+   "mrr@10": 1.0
+  },
+  {
+   "id": "q09",
+   "category": "phrase",
+   "query": "Grandma Lucas",
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+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "766de879-f9d0-4a07-b6df-b43ee13763d8",
+    "art-79042b8b-6192-440f-90b0-60708f7e6325"
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+   "mrr@10": 1.0
+  },
+  {
+   "id": "q10",
+   "category": "phrase",
+   "query": "Directed Harmonic",
+   "returned": [
+    "kn-5584ef9c-7f9d-4d7c-a10a-4ee6bc5cf356",
+    "ԍ????X????",
+    "bl-dcee1887-34c4-4ffa-9119-1e291685ba08",
+    "?ǚ?7??????",
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+    "knw-e24d6339-5ff3-4bed-ba53-707ffd0dc70a",
+    "mem-7eeacad7-d7c2-4c2b-8348-19a59aa6dbaf",
+    "????7???Ջ3",
+    "??????X??2c",
+    "g?e?7???'c?"
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+  {
+   "id": "q11",
+   "category": "phrase",
+   "query": "Sarah Bishop",
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+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "art-ddfcd045-2c3b-4a1e-9966-fec5ce44e1dd",
+    "? ?}&?#??X\b",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "766de879-f9d0-4a07-b6df-b43ee13763d8",
+    "mem-a9a9ce95-0d64-46eb-9db8-ff81d78ade35",
+    "mem-b8ecd23e-77ce-42f7-984c-f51453fec16d"
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+   "mrr@10": 0.2
+  },
+  {
+   "id": "q12",
+   "category": "phrase",
+   "query": "Directed Autonomous Runtime Modification",
+   "returned": [
+    "bl-5b17bd3b-0c41-46cb-a710-6fa4429692ff",
+    "bl-145a0985-2382-400f-a7c5-c335c5e30a72",
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+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "mem-e6327f52-2bda-4ce7-9471-2fffd1e172de",
+    "7?e?7???\f3?",
+    "?of?7???",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b"
+   ],
+   "n_returned": 9,
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+   "mrr@10": 1.0
+  },
+  {
+   "id": "q13",
+   "category": "phrase",
+   "query": "zero-knowledge encrypted backup",
+   "returned": [
+    "7774a16c-1027-4e3b-a21e-67f1f95a4acd",
+    "deda48cd-5e1a-46cb-bd43-8016afdb3a8a",
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+    "mem-a3c97012-5fa3-4915-a839-2c75c72005e0",
+    "mem-7cd90611-88a3-423d-a38a-0db2812952fa",
+    "bl-07375bf9-a169-42cd-adb3-7d32b25982f0",
+    "bl-ec84b63d-b278-4944-8d7f-4aa7a51c0315",
+    "7?e?7???\f3?",
+    "?of?7???",
+    "? ?}&?#??X\b"
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+  },
+  {
+   "id": "q14",
+   "category": "paraphrase",
+   "query": "the elderly relative who passed while he stayed away",
+   "returned": [
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "art-4a99aa1a-489b-4b43-958b-25217adb1aad",
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "????7???Ջ3",
+    "art-0f0277a1-4a8e-4645-95dd-fa379976f31c"
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+  },
+  {
+   "id": "q15",
+   "category": "paraphrase",
+   "query": "a soldier sidelined by illness who refused to quit",
+   "returned": [
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "art-2fabd873-d787-49cb-ad30-d4ed9fcff8ef",
+    "art-2f29ad36-6ee6-4a0e-8d72-0eaf7d12d3a9",
+    "? ?}&?#??X\b",
+    "kn-a31e1001-342e-4deb-a2e6-6d02d1f22dee",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "knw-9e74ee95-ba7d-49b1-9262-977eae9729d1",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b"
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+  },
+  {
+   "id": "q16",
+   "category": "paraphrase",
+   "query": "choosing an uncomfortable fact over a pleasant fiction",
+   "returned": [
+    "7?e?7???\f3?",
+    "? ?}&?#??X\b",
+    "kn-f8974b26-78a6-4aad-b893-19a73b20013d",
+    "?of?7???",
+    "????7???Ջ3",
+    "kn-d97920d0-1649-4223-9508-c0bb621e7fc0",
+    "kn-57b4c5e7-40c6-4c90-bf14-71841b0081d4",
+    "kn-9397c74b-35f3-4428-b4b0-5123353bbcd1",
+    "kn-81c24d13-a73b-4767-819c-dafaacc1498e",
+    "? ?}&?#??X\b"
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+  },
+  {
+   "id": "q17",
+   "category": "paraphrase",
+   "query": "a tight payload beats a bloated one",
+   "returned": [
+    "kn-d7c1e0fb-fa59-46d3-b4c9-a0d1d437a491",
+    "7?e?7???\f3?",
+    "? ?}&?#??X\b",
+    "kn-e8423822-eacf-4029-aa7b-10d4d28d621e",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "??o?'?B???k",
+    "kn-9397c74b-35f3-4428-b4b0-5123353bbcd1",
+    "? ?}&?#??X\b",
+    "?of?7???"
+   ],
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+  },
+  {
+   "id": "q18",
+   "category": "paraphrase",
+   "query": "if you are able and nobody is coming the job is yours",
+   "returned": [
+    "7?e?7???\f3?",
+    "?of?7???",
+    "imp-dce1da0f-8776-4a9e-972b-33411a7ca138",
+    "kn-5b606390-a52d-4ca2-8e0e-eba141d13440",
+    "kn-83bb86c6-521d-416c-a86e-6e29c2d8f102",
+    "kn-f8974b26-78a6-4aad-b893-19a73b20013d",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b"
+   ],
+   "n_returned": 9,
+   "latency_ms": 1352.5,
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+  },
+  {
+   "id": "q19",
+   "category": "paraphrase",
+   "query": "learning is the wealth creditors cannot seize",
+   "returned": [
+    "kn-5584ef9c-7f9d-4d7c-a10a-4ee6bc5cf356",
+    "knw-7902acca-604e-409b-8faf-ad85424211d0",
+    "knw-e24d6339-5ff3-4bed-ba53-707ffd0dc70a",
+    "kn-57b4c5e7-40c6-4c90-bf14-71841b0081d4",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "7?e?7???\f3?",
+    "??o?'?B???k",
+    "? ?}&?#??X\b",
+    "kn-0625e393-067c-4bba-8389-7e1b79265142",
+    "ע?RGk?\tH(?"
+   ],
+   "n_returned": 10,
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q20",
+   "category": "paraphrase",
+   "query": "reliability proven by track record not assertion",
+   "returned": [
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "7?e?7???\f3?",
+    "?of?7???",
+    "art-2fabd873-d787-49cb-ad30-d4ed9fcff8ef",
+    "kn-5584ef9c-7f9d-4d7c-a10a-4ee6bc5cf356"
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+  },
+  {
+   "id": "q21",
+   "category": "paraphrase",
+   "query": "boundaries that enable instead of confine",
+   "returned": [
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "??????X??2c",
+    "ԍ????X????",
+    "dR????X?-?S",
+    "kn-5584ef9c-7f9d-4d7c-a10a-4ee6bc5cf356",
+    "dz????Xƹ?i",
+    "kn-d7c1e0fb-fa59-46d3-b4c9-a0d1d437a491"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1327.3,
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q22",
+   "category": "paraphrase",
+   "query": "what shifts tells you where to cut a system apart",
+   "returned": [
+    "7?e?7???\f3?",
+    "kn-9397c74b-35f3-4428-b4b0-5123353bbcd1",
+    "?of?7???",
+    "kn-f8974b26-78a6-4aad-b893-19a73b20013d",
+    "knw-9e74ee95-ba7d-49b1-9262-977eae9729d1",
+    "dR????X?-?S",
+    "dz????Xƹ?i",
+    "ԍ????X????",
+    "??????X??2c",
+    "kn-d7c1e0fb-fa59-46d3-b4c9-a0d1d437a491"
+   ],
+   "n_returned": 10,
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q23",
+   "category": "paraphrase",
+   "query": "a mind that compounds instead of resetting each day",
+   "returned": [
+    "????7???Ջ3",
+    "kn-5584ef9c-7f9d-4d7c-a10a-4ee6bc5cf356",
+    "?ǚ?7??????",
+    "7?e?7???\f3?",
+    "??f?7???",
+    "? ?}&?#??X\b",
+    "%???2??jH??",
+    "kn-e8423822-eacf-4029-aa7b-10d4d28d621e",
+    "? ?}&?#??X\b",
+    "kn-9397c74b-35f3-4428-b4b0-5123353bbcd1"
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q24",
+   "category": "paraphrase",
+   "query": "loved for the unedited self and not the polished exterior",
+   "returned": [
+    "mem-bbb126a1-b297-42bb-86be-796871829c94",
+    "mem-45022957-2d78-48aa-a714-16d6eca52e0f",
+    "art-4a99aa1a-489b-4b43-958b-25217adb1aad",
+    "knw-35940684-abc4-42f0-b942-818f66b1f69a",
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "art-0f0277a1-4a8e-4645-95dd-fa379976f31c",
+    "art-ddfcd045-2c3b-4a1e-9966-fec5ce44e1dd",
+    "7?e?7???\f3?",
+    "? ?}&?#??X\b",
+    "'?T?a\"B~-?8"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1505.5,
+   "error": null,
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+   "recall@5": 0.0,
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+   "precision@5": 0.0,
+   "mrr@10": 0.0
+  },
+  {
+   "id": "q25",
+   "category": "paraphrase",
+   "query": "cheerfulness you arrive at instead of assuming",
+   "returned": [
+    "015644f5-8194-4af0-800d-dd4a0cd71396",
+    "?ǚ?7??????",
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "7?e?7???\f3?",
+    "kn-e8423822-eacf-4029-aa7b-10d4d28d621e",
+    "??S?7???",
+    "? ?}&?#??X\b",
+    "??f?7???",
+    "??S?7???",
+    "knw-5578cb21-e899-4822-b7f4-0d96fa094e3d"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1201.1,
+   "error": null,
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+   "recall@5": 0.0,
+   "recall@10": 0.0,
+   "precision@5": 0.0,
+   "mrr@10": 0.0
+  },
+  {
+   "id": "q26",
+   "category": "paraphrase",
+   "query": "a childhood offering no solid foundation to inherit",
+   "returned": [
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "7?e?7???\f3?",
+    "kn-e8423822-eacf-4029-aa7b-10d4d28d621e",
+    "? ?}&?#??X\b",
+    "??o?'?B???k",
+    "?of?7???",
+    "? ?}&?#??X\b"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1303.3,
+   "error": null,
+   "hit@5": 0.0,
+   "recall@5": 0.0,
+   "recall@10": 0.0,
+   "precision@5": 0.0,
+   "mrr@10": 0.0
+  },
+  {
+   "id": "q27",
+   "category": "associative",
+   "query": "Grandma Lucas stroke February 2006 goodbye window",
+   "returned": [
+    "? ?}&?#??X\b",
+    "? ?}&?#??X\b",
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+    "? ?}&?#??X\b",
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+}

tools/retrieval-eval/results-semseed-r2.json

@@ -0,0 +1,957 @@
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+   "mrr@10": 0.1111111111111111
+  },
+  {
+   "id": "q11",
+   "category": "phrase",
+   "query": "Sarah Bishop",
+   "returned": [
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+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
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+    "015644f5-8194-4af0-800d-dd4a0cd71396",
+    "art-ddfcd045-2c3b-4a1e-9966-fec5ce44e1dd",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "? ?}&?#??X\b",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "kn-6061318f-046b-4935-907d-8eafdce14930"
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+   "mrr@10": 0.1111111111111111
+  },
+  {
+   "id": "q12",
+   "category": "phrase",
+   "query": "Directed Autonomous Runtime Modification",
+   "returned": [
+    "bl-5b17bd3b-0c41-46cb-a710-6fa4429692ff",
+    "mem-e6327f52-2bda-4ce7-9471-2fffd1e172de",
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+    "mem-82b93b21-a865-410f-9ec1-fc54121d9bb5",
+    "bl-6f99e111-7055-4635-9831-a489747ce418",
+    "bl-967536a0-d49d-44fb-8cfb-b31b40bcbfae",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "bl-8b58d9bc-352b-4842-a7f8-a6254b5d1e25",
+    "bl-39cec462-c80c-4970-a3aa-91fe83053bde"
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+   "mrr@10": 1.0
+  },
+  {
+   "id": "q13",
+   "category": "phrase",
+   "query": "zero-knowledge encrypted backup",
+   "returned": [
+    "7774a16c-1027-4e3b-a21e-67f1f95a4acd",
+    "8f3abb0d-77ed-4af3-9f4d-ba62cd198886",
+    "deda48cd-5e1a-46cb-bd43-8016afdb3a8a",
+    "?",
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+    "?",
+    "mem-7cd90611-88a3-423d-a38a-0db2812952fa",
+    "?",
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+  {
+   "id": "q14",
+   "category": "paraphrase",
+   "query": "the elderly relative who passed while he stayed away",
+   "returned": [
+    "? ?}&?#??X\b",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "? ?}&?#??X\b",
+    "kn-0bb4f021-56de-4947-a35b-a37209e7ba21",
+    "? ?}&?#??X\b",
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+  {
+   "id": "q15",
+   "category": "paraphrase",
+   "query": "a soldier sidelined by illness who refused to quit",
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+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
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+    "art-2fabd873-d787-49cb-ad30-d4ed9fcff8ef",
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+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "? ?}&?#??X\b",
+    "54608b69-78b6-4239-b60f-b8206cfecacc",
+    "? ?}&?#??X\b"
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+  {
+   "id": "q16",
+   "category": "paraphrase",
+   "query": "choosing an uncomfortable fact over a pleasant fiction",
+   "returned": [
+    "7?e?7???\f3?",
+    "kn-13f60407-7b70-4db1-964f-ea1f8196efbd",
+    "knw-4aebd815-4eaf-49d7-954b-03595f3d48be",
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+    "knw-8fd9836c-cc39-49df-8d61-babda626cc88",
+    "?of?7???",
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+    "? ?}&?#??X\b",
+    "knw-d357b6bb-ad8a-4791-b516-426aea45fa5b",
+    "????7???Ջ3"
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+  {
+   "id": "q17",
+   "category": "paraphrase",
+   "query": "a tight payload beats a bloated one",
+   "returned": [
+    "kn-d7c1e0fb-fa59-46d3-b4c9-a0d1d437a491",
+    "knw-08559f5c-2306-4220-a146-398c74f1643c",
+    "7?e?7???\f3?",
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+    "kn-9397c74b-35f3-4428-b4b0-5123353bbcd1",
+    "knw-920c891f-bb8c-48c4-9afc-018ef12dcdc4",
+    "??o?'?B???k",
+    "knw-d357b6bb-ad8a-4791-b516-426aea45fa5b",
+    "? ?}&?#??X\b",
+    "knw-2c46cfb4-6d4e-4822-8a1a-7d743c1e4329"
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+  {
+   "id": "q18",
+   "category": "paraphrase",
+   "query": "if you are able and nobody is coming the job is yours",
+   "returned": [
+    "7?e?7???\f3?",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "?of?7???",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "imp-dce1da0f-8776-4a9e-972b-33411a7ca138",
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+    "kn-5b606390-a52d-4ca2-8e0e-eba141d13440",
+    "a1000001-0000-0000-0000-000000000001"
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+  {
+   "id": "q19",
+   "category": "paraphrase",
+   "query": "learning is the wealth creditors cannot seize",
+   "returned": [
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+    "kn-0bb4f021-56de-4947-a35b-a37209e7ba21",
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+  },
+  {
+   "id": "q20",
+   "category": "paraphrase",
+   "query": "reliability proven by track record not assertion",
+   "returned": [
+    "? ?}&?#??X\b",
+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "? ?}&?#??X\b",
+    "knw-f671966c-3387-4848-abca-b5deec122e00",
+    "knw-4aebd815-4eaf-49d7-954b-03595f3d48be",
+    "? ?}&?#??X\b",
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+    "knw-6b48dce2-f21c-452a-9db5-4e6aa61c87ca",
+    "? ?}&?#??X\b"
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+  },
+  {
+   "id": "q21",
+   "category": "paraphrase",
+   "query": "boundaries that enable instead of confine",
+   "returned": [
+    "? ?}&?#??X\b",
+    "kn-a5b3d0ac-f6a1-49a4-aebb-b8b4cd67fe83",
+    "bl-2515d870-e35e-443b-ba20-5150bbc73fed",
+    "? ?}&?#??X\b",
+    "project-Source_kn-6f248a50__Add_containment_rules__convergence__location-independence__failure_modes_",
+    "bl-8848929a-a23a-46bc-a2c7-fe3a3bc1cddf",
+    "? ?}&?#??X\b",
+    "bl-e93858c4-7cac-4b1a-bb62-490790d4c3f3",
+    "? ?}&?#??X\b",
+    "bl-286b562a-5299-40e0-a32a-afa9cbdfe995"
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+  },
+  {
+   "id": "q22",
+   "category": "paraphrase",
+   "query": "what shifts tells you where to cut a system apart",
+   "returned": [
+    "7?e?7???\f3?",
+    "kn-78db5396-3dbc-4481-bfc7-e4e1422feb1c",
+    "kn-9397c74b-35f3-4428-b4b0-5123353bbcd1",
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+    "knw-9e74ee95-ba7d-49b1-9262-977eae9729d1",
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+    "kn-a5b3d0ac-f6a1-49a4-aebb-b8b4cd67fe83",
+    "?of?7???",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8"
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+  },
+  {
+   "id": "q23",
+   "category": "paraphrase",
+   "query": "a mind that compounds instead of resetting each day",
+   "returned": [
+    "kn-5584ef9c-7f9d-4d7c-a10a-4ee6bc5cf356",
+    "mem-b43f6ef4-2f5a-418d-b5ce-3f21520cf6b8",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "????7???Ջ3",
+    "a1000001-0000-0000-0000-000000000001",
+    "8cbb60c5-4999-4ec1-8682-2592aedc4249",
+    "?ǚ?7??????",
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+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40",
+    "7?e?7???\f3?"
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+  },
+  {
+   "id": "q24",
+   "category": "paraphrase",
+   "query": "loved for the unedited self and not the polished exterior",
+   "returned": [
+    "mem-bbb126a1-b297-42bb-86be-796871829c94",
+    "knw-f9ce17a7-17fc-431f-8f23-695b670ec4fa",
+    "mem-45022957-2d78-48aa-a714-16d6eca52e0f",
+    "knw-2c46cfb4-6d4e-4822-8a1a-7d743c1e4329",
+    "art-4a99aa1a-489b-4b43-958b-25217adb1aad",
+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40",
+    "knw-35940684-abc4-42f0-b942-818f66b1f69a",
+    "knw-920c891f-bb8c-48c4-9afc-018ef12dcdc4",
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "a1000001-0000-0000-0000-000000000001"
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+  },
+  {
+   "id": "q25",
+   "category": "paraphrase",
+   "query": "cheerfulness you arrive at instead of assuming",
+   "returned": [
+    "?ǚ?7??????",
+    "knw-08559f5c-2306-4220-a146-398c74f1643c",
+    "015644f5-8194-4af0-800d-dd4a0cd71396",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "knw-d357b6bb-ad8a-4791-b516-426aea45fa5b",
+    "7?e?7???\f3?",
+    "ctx-bb74",
+    "??S?7???",
+    "knw-f671966c-3387-4848-abca-b5deec122e00"
+   ],
+   "n_returned": 10,
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q26",
+   "category": "paraphrase",
+   "query": "a childhood offering no solid foundation to inherit",
+   "returned": [
+    "? ?}&?#??X\b",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "kn-f230b362-b201-4402-9833-4160c89ab3d4",
+    "? ?}&?#??X\b",
+    "kn-6061318f-046b-4935-907d-8eafdce14930",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "? ?}&?#??X\b",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "kn-5b606390-a52d-4ca2-8e0e-eba141d13440",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3"
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+   "precision@5": 0.2,
+   "mrr@10": 0.2
+  },
+  {
+   "id": "q27",
+   "category": "associative",
+   "query": "Grandma Lucas stroke February 2006 goodbye window",
+   "returned": [
+    "? ?}&?#??X\b",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "? ?}&?#??X\b",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "kn-0bb4f021-56de-4947-a35b-a37209e7ba21",
+    "? ?}&?#??X\b",
+    "kn-e0423482-cfa5-4796-8689-8495c93b66bc",
+    "? ?}&?#??X\b",
+    "kn-78db5396-3dbc-4481-bfc7-e4e1422feb1c"
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+   "mrr@10": 0.3333333333333333
+  },
+  {
+   "id": "q28",
+   "category": "associative",
+   "query": "Marines hernia sepsis medical ward",
+   "returned": [
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "54608b69-78b6-4239-b60f-b8206cfecacc",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "bl-33ecccc2-e37f-43db-91b3-c2a86f08aaac",
+    "015644f5-8194-4af0-800d-dd4a0cd71396",
+    "art-ddfcd045-2c3b-4a1e-9966-fec5ce44e1dd",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "art-e0bdf5d8-d163-491f-b649-453fee8b721d",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71"
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+   "mrr@10": 0.25
+  },
+  {
+   "id": "q29",
+   "category": "associative",
+   "query": "Sarah Bishop Dyer trailer performance",
+   "returned": [
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "? ?}&?#??X\b",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "? ?}&?#??X\b",
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+    "? ?}&?#??X\b",
+    "015644f5-8194-4af0-800d-dd4a0cd71396",
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+   "mrr@10": 0.25
+  },
+  {
+   "id": "q30",
+   "category": "associative",
+   "query": "Swarm Architecture containment lateral worker",
+   "returned": [
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
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+    "bl-8c2d5f51-3ccd-4c2e-848a-eb60d90a3b98"
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+  {
+   "id": "q31",
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+   "query": "hope won inside the narrative preface",
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+  },
+  {
+   "id": "q32",
+   "category": "associative",
+   "query": "man of the house six years old expectation",
+   "returned": [
+    "? ?}&?#??X\b",
+    "4f698ae6-c40e-464e-9798-50350991a188",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
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+    "? ?}&?#??X\b",
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+  {
+   "id": "q33",
+   "category": "nonsense",
+   "query": "zqxjvw plimforth grebulon",
+   "returned": [],
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+   "error": null,
+   "clean": true,
+   "false_positives": 0
+  },
+  {
+   "id": "q34",
+   "category": "nonsense",
+   "query": "flarnbistle quommetry",
+   "returned": [],
+   "n_returned": 0,
+   "latency_ms": 510.6,
+   "error": null,
+   "clean": true,
+   "false_positives": 0
+  },
+  {
+   "id": "q35",
+   "category": "nonsense",
+   "query": "xxqzzt vurblenacht throom",
+   "returned": [
+    "art-4a99aa1a-489b-4b43-958b-25217adb1aad",
+    "?V?",
+    "knw-6b48dce2-f21c-452a-9db5-4e6aa61c87ca",
+    "knw-920c891f-bb8c-48c4-9afc-018ef12dcdc4",
+    "?m?\\}Q??6??",
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+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "?m?\\}Q??6??",
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+  },
+  {
+   "id": "q36",
+   "category": "superseded",
+   "query": "is the self-improvement architecture called DARMA or DHARMA",
+   "returned": [
+    "7?e?7???\f3?",
+    "mem-80d7416b-20e9-48a0-b176-b215527e2f56",
+    "? ?}&?#??X\b",
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+  {
+   "id": "q37",
+   "category": "superseded",
+   "query": "how many provisional patents does Will actually have",
+   "returned": [
+    "? ?}&?#??X\b",
+    "12082f7e-e320-438b-bd65-083d8259748f",
+    "6de314bf-5c4c-4cfc-871f-fa2e422d45e6",
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+    "? ?}&?#??X\b",
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+    "? ?}&?#??X\b"
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+  {
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+    "bl-7328cbe3-0200-43c2-88e7-0a164e15fca4",
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+    "7?e?7???\f3?",
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+    "bl-4f7b651b-6b33-449c-8a3b-cfce12ce984b",
+    "%???2??jH??"
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+ ]
+}

tools/retrieval-eval/results-semseed.json

@@ -0,0 +1,957 @@
+{
+ "label": "semseed",
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+ "soul_md5": "ab0c82781215f43d4907bd6f39d3615b",
+ "corpus": "/Users/timlingo/neuron-eval-corpora/snapshot-pre-repair-20260806-embedded.json",
+ "corpus_nodes": 78768,
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+ "gold_set": "/Users/timlingo/Development/neuron-technologies/_wt-semseed/tools/retrieval-eval/gold_set.json",
+ "limit": 10,
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+  {
+   "id": "q02",
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+    "project-engram",
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+  {
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+   "query": "cartabandonedevent",
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+  },
+  {
+   "id": "q07",
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+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
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+  {
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+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
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+    "kn-6061318f-046b-4935-907d-8eafdce14930",
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+    "? ?}&?#??X\b",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "? ?}&?#??X\b",
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+  },
+  {
+   "id": "q10",
+   "category": "phrase",
+   "query": "Directed Harmonic",
+   "returned": [
+    "ԍ????X????",
+    "project-harmonic-framework",
+    "?ǚ?7??????",
+    "project-harmonic-framework_com",
+    "knw-e24d6339-5ff3-4bed-ba53-707ffd0dc70a",
+    "??????X??2c",
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+    "????7???Ջ3",
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+  {
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+   "precision@5": 0.0,
+   "mrr@10": 0.1111111111111111
+  },
+  {
+   "id": "q12",
+   "category": "phrase",
+   "query": "Directed Autonomous Runtime Modification",
+   "returned": [
+    "bl-5b17bd3b-0c41-46cb-a710-6fa4429692ff",
+    "mem-e6327f52-2bda-4ce7-9471-2fffd1e172de",
+    "bl-31abf75b-998f-4a4f-a6dd-8204119e0451",
+    "bl-145a0985-2382-400f-a7c5-c335c5e30a72",
+    "mem-82b93b21-a865-410f-9ec1-fc54121d9bb5",
+    "bl-6f99e111-7055-4635-9831-a489747ce418",
+    "bl-967536a0-d49d-44fb-8cfb-b31b40bcbfae",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "bl-8b58d9bc-352b-4842-a7f8-a6254b5d1e25",
+    "bl-39cec462-c80c-4970-a3aa-91fe83053bde"
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+   "precision@5": 0.8,
+   "mrr@10": 1.0
+  },
+  {
+   "id": "q13",
+   "category": "phrase",
+   "query": "zero-knowledge encrypted backup",
+   "returned": [
+    "7774a16c-1027-4e3b-a21e-67f1f95a4acd",
+    "8f3abb0d-77ed-4af3-9f4d-ba62cd198886",
+    "deda48cd-5e1a-46cb-bd43-8016afdb3a8a",
+    "?",
+    "mem-dba009a2-d2ea-4f5a-b9e8-0f04bc9ab32f",
+    "?",
+    "mem-7cd90611-88a3-423d-a38a-0db2812952fa",
+    "?",
+    "bl-07375bf9-a169-42cd-adb3-7d32b25982f0",
+    "?"
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+   "n_returned": 10,
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+   "recall@5": 1.0,
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+   "mrr@10": 0.3333333333333333
+  },
+  {
+   "id": "q14",
+   "category": "paraphrase",
+   "query": "the elderly relative who passed while he stayed away",
+   "returned": [
+    "? ?}&?#??X\b",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "? ?}&?#??X\b",
+    "kn-0bb4f021-56de-4947-a35b-a37209e7ba21",
+    "? ?}&?#??X\b",
+    "kn-6061318f-046b-4935-907d-8eafdce14930",
+    "art-4a99aa1a-489b-4b43-958b-25217adb1aad",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "ctx-4a41"
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+  },
+  {
+   "id": "q15",
+   "category": "paraphrase",
+   "query": "a soldier sidelined by illness who refused to quit",
+   "returned": [
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "art-2f29ad36-6ee6-4a0e-8d72-0eaf7d12d3a9",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "art-2fabd873-d787-49cb-ad30-d4ed9fcff8ef",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "kn-a31e1001-342e-4deb-a2e6-6d02d1f22dee",
+    "54608b69-78b6-4239-b60f-b8206cfecacc",
+    "knw-9e74ee95-ba7d-49b1-9262-977eae9729d1"
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+   "mrr@10": 0.5
+  },
+  {
+   "id": "q16",
+   "category": "paraphrase",
+   "query": "choosing an uncomfortable fact over a pleasant fiction",
+   "returned": [
+    "7?e?7???\f3?",
+    "kn-13f60407-7b70-4db1-964f-ea1f8196efbd",
+    "knw-4aebd815-4eaf-49d7-954b-03595f3d48be",
+    "kn-f8974b26-78a6-4aad-b893-19a73b20013d",
+    "knw-8fd9836c-cc39-49df-8d61-babda626cc88",
+    "?of?7???",
+    "knw-e94982a2-358d-4f2f-af31-8ee0fcec07c6",
+    "? ?}&?#??X\b",
+    "knw-d357b6bb-ad8a-4791-b516-426aea45fa5b",
+    "????7???Ջ3"
+   ],
+   "n_returned": 10,
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+   "precision@5": 0.2,
+   "mrr@10": 0.5
+  },
+  {
+   "id": "q17",
+   "category": "paraphrase",
+   "query": "a tight payload beats a bloated one",
+   "returned": [
+    "kn-d7c1e0fb-fa59-46d3-b4c9-a0d1d437a491",
+    "knw-08559f5c-2306-4220-a146-398c74f1643c",
+    "7?e?7???\f3?",
+    "knw-f6ed7d00-bf7d-42ce-9e40-77cf3406e918",
+    "??o?'?B???k",
+    "knw-920c891f-bb8c-48c4-9afc-018ef12dcdc4",
+    "? ?}&?#??X\b",
+    "knw-d357b6bb-ad8a-4791-b516-426aea45fa5b",
+    "? ?}&?#??X\b",
+    "knw-2c46cfb4-6d4e-4822-8a1a-7d743c1e4329"
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+   "n_returned": 10,
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q18",
+   "category": "paraphrase",
+   "query": "if you are able and nobody is coming the job is yours",
+   "returned": [
+    "7?e?7???\f3?",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "?of?7???",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "imp-dce1da0f-8776-4a9e-972b-33411a7ca138",
+    "ctx-cc7f",
+    "ctx-4a41",
+    "kn-5b606390-a52d-4ca2-8e0e-eba141d13440",
+    "a1000001-0000-0000-0000-000000000001"
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+   "mrr@10": 0.5
+  },
+  {
+   "id": "q19",
+   "category": "paraphrase",
+   "query": "learning is the wealth creditors cannot seize",
+   "returned": [
+    "knw-e24d6339-5ff3-4bed-ba53-707ffd0dc70a",
+    "kn-0bb4f021-56de-4947-a35b-a37209e7ba21",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "kn-f230b362-b201-4402-9833-4160c89ab3d4",
+    "knw-7902acca-604e-409b-8faf-ad85424211d0",
+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40",
+    "kn-57b4c5e7-40c6-4c90-bf14-71841b0081d4",
+    "knw-ed33e669-0790-44cb-a036-958d605c6fea",
+    "kn-5584ef9c-7f9d-4d7c-a10a-4ee6bc5cf356",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e"
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+   "mrr@10": 0.5
+  },
+  {
+   "id": "q20",
+   "category": "paraphrase",
+   "query": "reliability proven by track record not assertion",
+   "returned": [
+    "? ?}&?#??X\b",
+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "? ?}&?#??X\b",
+    "knw-f671966c-3387-4848-abca-b5deec122e00",
+    "knw-4aebd815-4eaf-49d7-954b-03595f3d48be",
+    "? ?}&?#??X\b",
+    "a708dd6e-fe73-4f2f-a21e-89daa0985487",
+    "knw-6b48dce2-f21c-452a-9db5-4e6aa61c87ca",
+    "? ?}&?#??X\b"
+   ],
+   "n_returned": 10,
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+   "precision@5": 0.2,
+   "mrr@10": 0.5
+  },
+  {
+   "id": "q21",
+   "category": "paraphrase",
+   "query": "boundaries that enable instead of confine",
+   "returned": [
+    "? ?}&?#??X\b",
+    "kn-a5b3d0ac-f6a1-49a4-aebb-b8b4cd67fe83",
+    "bl-2515d870-e35e-443b-ba20-5150bbc73fed",
+    "? ?}&?#??X\b",
+    "project-Source_kn-6f248a50__Add_containment_rules__convergence__location-independence__failure_modes_",
+    "bl-8848929a-a23a-46bc-a2c7-fe3a3bc1cddf",
+    "? ?}&?#??X\b",
+    "bl-e93858c4-7cac-4b1a-bb62-490790d4c3f3",
+    "? ?}&?#??X\b",
+    "bl-286b562a-5299-40e0-a32a-afa9cbdfe995"
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+   "mrr@10": 0.5
+  },
+  {
+   "id": "q22",
+   "category": "paraphrase",
+   "query": "what shifts tells you where to cut a system apart",
+   "returned": [
+    "7?e?7???\f3?",
+    "kn-78db5396-3dbc-4481-bfc7-e4e1422feb1c",
+    "knw-9e74ee95-ba7d-49b1-9262-977eae9729d1",
+    "kn-0bb4f021-56de-4947-a35b-a37209e7ba21",
+    "kn-f8974b26-78a6-4aad-b893-19a73b20013d",
+    "kn-6061318f-046b-4935-907d-8eafdce14930",
+    "kn-9397c74b-35f3-4428-b4b0-5123353bbcd1",
+    "kn-a5b3d0ac-f6a1-49a4-aebb-b8b4cd67fe83",
+    "?of?7???",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8"
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+   "mrr@10": 0.5
+  },
+  {
+   "id": "q23",
+   "category": "paraphrase",
+   "query": "a mind that compounds instead of resetting each day",
+   "returned": [
+    "kn-5584ef9c-7f9d-4d7c-a10a-4ee6bc5cf356",
+    "mem-b43f6ef4-2f5a-418d-b5ce-3f21520cf6b8",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "????7???Ջ3",
+    "a1000001-0000-0000-0000-000000000001",
+    "8cbb60c5-4999-4ec1-8682-2592aedc4249",
+    "?ǚ?7??????",
+    "mem-024598a9-ed2e-4eeb-b1e1-5410856ff132",
+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40",
+    "7?e?7???\f3?"
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+  },
+  {
+   "id": "q24",
+   "category": "paraphrase",
+   "query": "loved for the unedited self and not the polished exterior",
+   "returned": [
+    "mem-bbb126a1-b297-42bb-86be-796871829c94",
+    "knw-f9ce17a7-17fc-431f-8f23-695b670ec4fa",
+    "mem-45022957-2d78-48aa-a714-16d6eca52e0f",
+    "knw-2c46cfb4-6d4e-4822-8a1a-7d743c1e4329",
+    "art-4a99aa1a-489b-4b43-958b-25217adb1aad",
+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40",
+    "knw-35940684-abc4-42f0-b942-818f66b1f69a",
+    "knw-920c891f-bb8c-48c4-9afc-018ef12dcdc4",
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "a1000001-0000-0000-0000-000000000001"
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+   "n_returned": 10,
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+   "recall@5": 0.0,
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q25",
+   "category": "paraphrase",
+   "query": "cheerfulness you arrive at instead of assuming",
+   "returned": [
+    "?ǚ?7??????",
+    "knw-08559f5c-2306-4220-a146-398c74f1643c",
+    "015644f5-8194-4af0-800d-dd4a0cd71396",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "knw-d357b6bb-ad8a-4791-b516-426aea45fa5b",
+    "7?e?7???\f3?",
+    "ctx-bb74",
+    "??S?7???",
+    "knw-f671966c-3387-4848-abca-b5deec122e00"
+   ],
+   "n_returned": 10,
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q26",
+   "category": "paraphrase",
+   "query": "a childhood offering no solid foundation to inherit",
+   "returned": [
+    "? ?}&?#??X\b",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "kn-f230b362-b201-4402-9833-4160c89ab3d4",
+    "? ?}&?#??X\b",
+    "kn-6061318f-046b-4935-907d-8eafdce14930",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "? ?}&?#??X\b",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "kn-5b606390-a52d-4ca2-8e0e-eba141d13440",
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3"
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+   "precision@5": 0.2,
+   "mrr@10": 0.2
+  },
+  {
+   "id": "q27",
+   "category": "associative",
+   "query": "Grandma Lucas stroke February 2006 goodbye window",
+   "returned": [
+    "? ?}&?#??X\b",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "? ?}&?#??X\b",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "kn-0bb4f021-56de-4947-a35b-a37209e7ba21",
+    "? ?}&?#??X\b",
+    "kn-e0423482-cfa5-4796-8689-8495c93b66bc",
+    "? ?}&?#??X\b",
+    "kn-78db5396-3dbc-4481-bfc7-e4e1422feb1c"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1530.5,
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+   "recall@5": 0.18181818181818182,
+   "recall@10": 0.45454545454545453,
+   "precision@5": 0.4,
+   "mrr@10": 0.3333333333333333
+  },
+  {
+   "id": "q28",
+   "category": "associative",
+   "query": "Marines hernia sepsis medical ward",
+   "returned": [
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "54608b69-78b6-4239-b60f-b8206cfecacc",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "bl-33ecccc2-e37f-43db-91b3-c2a86f08aaac",
+    "015644f5-8194-4af0-800d-dd4a0cd71396",
+    "art-ddfcd045-2c3b-4a1e-9966-fec5ce44e1dd",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "art-e0bdf5d8-d163-491f-b649-453fee8b721d",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71"
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+   "n_returned": 10,
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+   "mrr@10": 0.25
+  },
+  {
+   "id": "q29",
+   "category": "associative",
+   "query": "Sarah Bishop Dyer trailer performance",
+   "returned": [
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "? ?}&?#??X\b",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "? ?}&?#??X\b",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "? ?}&?#??X\b",
+    "015644f5-8194-4af0-800d-dd4a0cd71396",
+    "art-4a99aa1a-489b-4b43-958b-25217adb1aad",
+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40"
+   ],
+   "n_returned": 10,
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+   "recall@5": 0.09090909090909091,
+   "recall@10": 0.36363636363636365,
+   "precision@5": 0.2,
+   "mrr@10": 0.25
+  },
+  {
+   "id": "q30",
+   "category": "associative",
+   "query": "Swarm Architecture containment lateral worker",
+   "returned": [
+    "art-ee615cdb-e599-423d-9a4d-977859390ed3",
+    "bl-9bde67c1-f0ba-4c3a-8fe5-de0deee0ce43",
+    "ctx-e5427d7d",
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+    "bl-2515d870-e35e-443b-ba20-5150bbc73fed",
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+    "ctx-bb74",
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+    "bl-8c2d5f51-3ccd-4c2e-848a-eb60d90a3b98"
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+  {
+   "id": "q31",
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+   "query": "hope won inside the narrative preface",
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+    "knw-e94982a2-358d-4f2f-af31-8ee0fcec07c6",
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+  },
+  {
+   "id": "q32",
+   "category": "associative",
+   "query": "man of the house six years old expectation",
+   "returned": [
+    "? ?}&?#??X\b",
+    "4f698ae6-c40e-464e-9798-50350991a188",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
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+    "? ?}&?#??X\b",
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+    "? ?}&?#??X\b",
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+    "? ?}&?#??X\b",
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+  {
+   "id": "q33",
+   "category": "nonsense",
+   "query": "zqxjvw plimforth grebulon",
+   "returned": [],
+   "n_returned": 0,
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+   "error": null,
+   "clean": true,
+   "false_positives": 0
+  },
+  {
+   "id": "q34",
+   "category": "nonsense",
+   "query": "flarnbistle quommetry",
+   "returned": [],
+   "n_returned": 0,
+   "latency_ms": 517.1,
+   "error": null,
+   "clean": true,
+   "false_positives": 0
+  },
+  {
+   "id": "q35",
+   "category": "nonsense",
+   "query": "xxqzzt vurblenacht throom",
+   "returned": [
+    "art-4a99aa1a-489b-4b43-958b-25217adb1aad",
+    "?V?",
+    "knw-6b48dce2-f21c-452a-9db5-4e6aa61c87ca",
+    "knw-920c891f-bb8c-48c4-9afc-018ef12dcdc4",
+    "?m?\\}Q??6??",
+    "8cbb60c5-4999-4ec1-8682-2592aedc4249",
+    "art-79042b8b-6192-440f-90b0-60708f7e6325",
+    "?m?\\}Q??6??",
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+   "error": null,
+   "clean": false,
+   "false_positives": 10
+  },
+  {
+   "id": "q36",
+   "category": "superseded",
+   "query": "is the self-improvement architecture called DARMA or DHARMA",
+   "returned": [
+    "7?e?7???\f3?",
+    "mem-80d7416b-20e9-48a0-b176-b215527e2f56",
+    "? ?}&?#??X\b",
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+    "?of?7???",
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+  },
+  {
+   "id": "q37",
+   "category": "superseded",
+   "query": "how many provisional patents does Will actually have",
+   "returned": [
+    "? ?}&?#??X\b",
+    "12082f7e-e320-438b-bd65-083d8259748f",
+    "6de314bf-5c4c-4cfc-871f-fa2e422d45e6",
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+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40",
+    "? ?}&?#??X\b"
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+  {
+   "id": "q38",
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+   "query": "is MCP still the live integration layer",
+   "returned": [
+    "kn-5584ef9c-7f9d-4d7c-a10a-4ee6bc5cf356",
+    "bl-7328cbe3-0200-43c2-88e7-0a164e15fca4",
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+    "? ?}&?#??X\b",
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+    "bl-4f7b651b-6b33-449c-8a3b-cfce12ce984b",
+    "%???2??jH??"
+   ],
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+ ]
+}

tools/retrieval-eval/results-wordstart-r2.json

@@ -0,0 +1,948 @@
+{
+ "label": "wordstart-r2",
+ "soul_binary": "/private/tmp/claude-501/-Users-timlingo/82369039-a20e-4b5a-8a5e-28234a57b996/scratchpad/soul-wordstart",
+ "soul_md5": "32d4cf77672658a5f49dc7c9213e3ba2",
+ "corpus": "/Users/timlingo/neuron-eval-corpora/snapshot-pre-repair-20260806-embedded.json",
+ "corpus_nodes": 78768,
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+ "gold_set": "/Users/timlingo/Development/neuron-technologies/_wt-eval/tools/retrieval-eval/gold_set.json",
+ "limit": 10,
+ "port": 7895,
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+ "rows": [
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+  {
+   "id": "q02",
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+   "query": "engram-migrate",
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+    "bl-b28d7256-6f74-4567-bd90-40d0ef2a6d78",
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+  {
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+   "query": "cartabandonedevent",
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+  },
+  {
+   "id": "q07",
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+    "mem-a4a9dfc3-e40b-49b3-b1e1-060e8be2f482",
+    "project-Imprint__system_design__ADRs__tech_strategy__integration_patterns__governance_",
+    "project-Imprint__analysis_patterns__data_storytelling__SQL__dashboards__insight_framing_",
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+  },
+  {
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+   "query": "Directed Harmonic",
+   "returned": [
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+    "project-harmonic-framework",
+    "bl-798d135f-3987-4ccd-8de6-70ca2f358337",
+    "mem-7eeacad7-d7c2-4c2b-8348-19a59aa6dbaf",
+    "project-harmonic-framework_com",
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+    "tag-harmonic-design",
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+  },
+  {
+   "id": "q12",
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+   "query": "Directed Autonomous Runtime Modification",
+   "returned": [
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+    "bl-967536a0-d49d-44fb-8cfb-b31b40bcbfae",
+    "bl-8b58d9bc-352b-4842-a7f8-a6254b5d1e25",
+    "?Q??m?;?u?'",
+    "bl-39cec462-c80c-4970-a3aa-91fe83053bde"
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+   "mrr@10": 1.0
+  },
+  {
+   "id": "q13",
+   "category": "phrase",
+   "query": "zero-knowledge encrypted backup",
+   "returned": [
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+    "8f3abb0d-77ed-4af3-9f4d-ba62cd198886",
+    "7774a16c-1027-4e3b-a21e-67f1f95a4acd",
+    "?",
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+    "?",
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+  {
+   "id": "q14",
+   "category": "paraphrase",
+   "query": "the elderly relative who passed while he stayed away",
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+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
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+  {
+   "id": "q15",
+   "category": "paraphrase",
+   "query": "a soldier sidelined by illness who refused to quit",
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+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
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+  {
+   "id": "q16",
+   "category": "paraphrase",
+   "query": "choosing an uncomfortable fact over a pleasant fiction",
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+    "knw-4aebd815-4eaf-49d7-954b-03595f3d48be",
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+  {
+   "id": "q17",
+   "category": "paraphrase",
+   "query": "a tight payload beats a bloated one",
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+    "bl-798d135f-3987-4ccd-8de6-70ca2f358337",
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+  {
+   "id": "q18",
+   "category": "paraphrase",
+   "query": "if you are able and nobody is coming the job is yours",
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+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
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+  {
+   "id": "q19",
+   "category": "paraphrase",
+   "query": "learning is the wealth creditors cannot seize",
+   "returned": [
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+    "knw-7902acca-604e-409b-8faf-ad85424211d0",
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+  {
+   "id": "q20",
+   "category": "paraphrase",
+   "query": "reliability proven by track record not assertion",
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+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40",
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+  {
+   "id": "q21",
+   "category": "paraphrase",
+   "query": "boundaries that enable instead of confine",
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+    "project-Source_kn-6f248a50__Add_containment_rules__convergence__location-independence__failure_modes_",
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+  {
+   "id": "q22",
+   "category": "paraphrase",
+   "query": "what shifts tells you where to cut a system apart",
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+  {
+   "id": "q23",
+   "category": "paraphrase",
+   "query": "a mind that compounds instead of resetting each day",
+   "returned": [
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+    "mem-b43f6ef4-2f5a-418d-b5ce-3f21520cf6b8",
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+  {
+   "id": "q24",
+   "category": "paraphrase",
+   "query": "loved for the unedited self and not the polished exterior",
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+  },
+  {
+   "id": "q25",
+   "category": "paraphrase",
+   "query": "cheerfulness you arrive at instead of assuming",
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+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
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+  {
+   "id": "q26",
+   "category": "paraphrase",
+   "query": "a childhood offering no solid foundation to inherit",
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+    "tag-childhood",
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+  {
+   "id": "q27",
+   "category": "associative",
+   "query": "Grandma Lucas stroke February 2006 goodbye window",
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+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
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+  {
+   "id": "q28",
+   "category": "associative",
+   "query": "Marines hernia sepsis medical ward",
+   "returned": [
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+    "54608b69-78b6-4239-b60f-b8206cfecacc",
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+  {
+   "id": "q29",
+   "category": "associative",
+   "query": "Sarah Bishop Dyer trailer performance",
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+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
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+    "tag-trailer-park-paladins",
+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40",
+    "project-trailer-park-paladins",
+    "kn-78db5396-3dbc-4481-bfc7-e4e1422feb1c"
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+   "precision@5": 0.4,
+   "mrr@10": 0.5
+  },
+  {
+   "id": "q30",
+   "category": "associative",
+   "query": "Swarm Architecture containment lateral worker",
+   "returned": [
+    "bl-0fac287f-f4c0-4f15-bc4d-ff7f8a7af3ae",
+    "bl-9bde67c1-f0ba-4c3a-8fe5-de0deee0ce43",
+    "bl-2515d870-e35e-443b-ba20-5150bbc73fed",
+    "kn-a5b3d0ac-f6a1-49a4-aebb-b8b4cd67fe83",
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+    "bl-fc6fcb0b-9e4b-40bf-8e88-dbfe4e27c31a",
+    "kn-6f248a50-355b-47bb-aec8-e0e646a9b077",
+    "kn-6061318f-046b-4935-907d-8eafdce14930",
+    "mem-ab34c2f7-3243-424b-affa-25555f6cf9cc"
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q31",
+   "category": "associative",
+   "query": "hope won inside the narrative preface",
+   "returned": [
+    "kn-e0423482-cfa5-4796-8689-8495c93b66bc",
+    "knw-e94982a2-358d-4f2f-af31-8ee0fcec07c6",
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+    "knw-723551f5-1950-42a3-8b89-b6a06913cef0",
+    "tag-hope",
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+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e"
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+   "mrr@10": 0.25
+  },
+  {
+   "id": "q32",
+   "category": "associative",
+   "query": "man of the house six years old expectation",
+   "returned": [
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "knw-528dbc37-eabc-4b75-a7a5-65bf38d6018a",
+    "knw-d357b6bb-ad8a-4791-b516-426aea45fa5b",
+    "knw-473f3f24-20f6-4f39-8589-3709538eb6ac",
+    "mem-a0b7cfda-bc9e-4f40-b9a9-1722cf3f8263",
+    "knw-7902acca-604e-409b-8faf-ad85424211d0",
+    "knw-35940684-abc4-42f0-b942-818f66b1f69a",
+    "4f698ae6-c40e-464e-9798-50350991a188",
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+    "kn-6061318f-046b-4935-907d-8eafdce14930"
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+   "precision@5": 0.0,
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+  },
+  {
+   "id": "q33",
+   "category": "nonsense",
+   "query": "zqxjvw plimforth grebulon",
+   "returned": [],
+   "n_returned": 0,
+   "latency_ms": 350.7,
+   "error": null,
+   "clean": true,
+   "false_positives": 0
+  },
+  {
+   "id": "q34",
+   "category": "nonsense",
+   "query": "flarnbistle quommetry",
+   "returned": [],
+   "n_returned": 0,
+   "latency_ms": 254.6,
+   "error": null,
+   "clean": true,
+   "false_positives": 0
+  },
+  {
+   "id": "q35",
+   "category": "nonsense",
+   "query": "xxqzzt vurblenacht throom",
+   "returned": [],
+   "n_returned": 0,
+   "latency_ms": 345.8,
+   "error": null,
+   "clean": true,
+   "false_positives": 0
+  },
+  {
+   "id": "q36",
+   "category": "superseded",
+   "query": "is the self-improvement architecture called DARMA or DHARMA",
+   "returned": [
+    "mem-f3b37427-b7d1-4f7e-b32c-0241a20ce8da",
+    "mem-80d7416b-20e9-48a0-b176-b215527e2f56",
+    "tag-__darma____cgi____patents____self-improvement____character-preservation____autonomous____architecture__",
+    "kn-b7e98d63-8b83-4911-b4d0-990602a7f575",
+    "tag-__darma____cgi____patents____self-improvement____character-preservation____autonomous____kotlin____architecture__",
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+   "rank_correct": 2,
+   "rank_stale": 8
+  },
+  {
+   "id": "q37",
+   "category": "superseded",
+   "query": "how many provisional patents does Will actually have",
+   "returned": [
+    "mem-6f0b2b45-90c1-4356-ac01-3daac05b09c8",
+    "12082f7e-e320-438b-bd65-083d8259748f",
+    "015644f5-8194-4af0-800d-dd4a0cd71396",
+    "13705072-4515-4124-963d-083af490494f",
+    "527ecb25-2587-47eb-8269-73be2431abd4",
+    "6de314bf-5c4c-4cfc-871f-fa2e422d45e6",
+    "a1000001-0000-0000-0000-000000000002",
+    "3cf706a1-3825-45d8-b0a9-06cae6cdf5b8",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "de3b6428-b76c-4c44-90e0-bf1dd6998027"
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+   "rank_correct": 8,
+   "rank_stale": null
+  },
+  {
+   "id": "q38",
+   "category": "superseded",
+   "query": "is MCP still the live integration layer",
+   "returned": [
+    "5fcba804-eb5b-48ec-82da-146b1c6bb50d",
+    "bl-7328cbe3-0200-43c2-88e7-0a164e15fca4",
+    "bl-c8c19362-430b-4817-9cf4-9e85e0099c64",
+    "bl-c5c6571e-118f-47c7-8cbb-3ed0ebf64a51",
+    "mem-101e81b4-8097-4749-8d8d-7bb66de34517",
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+    "bl-4f7b651b-6b33-449c-8a3b-cfce12ce984b",
+    "mem-3a2cf162-d93b-4f29-86f2-5066fb7fe1f5"
+   ],
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+   "rank_correct": null,
+   "rank_stale": 5
+  }
+ ]
+}

tools/retrieval-eval/results-wordstart.json

@@ -0,0 +1,948 @@
+{
+ "label": "wordstart",
+ "soul_binary": "/private/tmp/claude-501/-Users-timlingo/82369039-a20e-4b5a-8a5e-28234a57b996/scratchpad/soul-wordstart",
+ "soul_md5": "32d4cf77672658a5f49dc7c9213e3ba2",
+ "corpus": "/Users/timlingo/neuron-eval-corpora/snapshot-pre-repair-20260806-embedded.json",
+ "corpus_nodes": 78768,
+ "corpus_edges": 14214,
+ "gold_set": "/Users/timlingo/Development/neuron-technologies/_wt-eval/tools/retrieval-eval/gold_set.json",
+ "limit": 10,
+ "port": 7894,
+ "wall_clock_s": 28.9,
+ "child_pid": 1420,
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+ "rows": [
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+   "category": "exact_rare",
+   "query": "unjailbreakable",
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+  },
+  {
+   "id": "q02",
+   "category": "exact_rare",
+   "query": "engram-migrate",
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+    "bl-ba764d70-e9d7-4f62-848f-719cb665f45e",
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+    "bl-b28d7256-6f74-4567-bd90-40d0ef2a6d78",
+    "project-engram",
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+    "project-engram-lang",
+    "ctx-175f",
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+  {
+   "id": "q03",
+   "category": "exact_rare",
+   "query": "cartabandonedevent",
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+  {
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+  {
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+   "query": "inferencenodemanager",
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+    "bl-c1765767-3e27-449a-8c94-10411d1eb7c0",
+    "project-Add_inference_url_config_to_Neuron_MCP__Route_summarization_gen_tasks_to_Pantheon__keep_frontier_for_complex_reasoning_"
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+   "mrr@10": 1.0
+  },
+  {
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+  },
+  {
+   "id": "q07",
+   "category": "phrase",
+   "query": "patterns not returns",
+   "returned": [
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+    "mem-a4a9dfc3-e40b-49b3-b1e1-060e8be2f482",
+    "project-Imprint__system_design__ADRs__tech_strategy__integration_patterns__governance_",
+    "project-Imprint__analysis_patterns__data_storytelling__SQL__dashboards__insight_framing_",
+    "bl-79028eed-c330-4724-9402-734062d13503",
+    "bl-39dad13d-7105-4049-8224-dc3c34fdb1f3",
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+    "knw-7902acca-604e-409b-8faf-ad85424211d0",
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+  {
+   "id": "q09",
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+   "query": "Grandma Lucas",
+   "returned": [
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+   "mrr@10": 1.0
+  },
+  {
+   "id": "q10",
+   "category": "phrase",
+   "query": "Directed Harmonic",
+   "returned": [
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+    "project-harmonic-framework",
+    "bl-798d135f-3987-4ccd-8de6-70ca2f358337",
+    "mem-7eeacad7-d7c2-4c2b-8348-19a59aa6dbaf",
+    "project-harmonic-framework_com",
+    "bl-680b24a9-edc3-4a9d-847a-bff0b46b568c",
+    "tag-harmonic-design",
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+    "tag-harmonic-framework",
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+  },
+  {
+   "id": "q11",
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+   "query": "Sarah Bishop",
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+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
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+   "mrr@10": 1.0
+  },
+  {
+   "id": "q12",
+   "category": "phrase",
+   "query": "Directed Autonomous Runtime Modification",
+   "returned": [
+    "mem-e6327f52-2bda-4ce7-9471-2fffd1e172de",
+    "bl-31abf75b-998f-4a4f-a6dd-8204119e0451",
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+    "bl-8b58d9bc-352b-4842-a7f8-a6254b5d1e25",
+    "?Q??m?;?u?'",
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+   "id": "q13",
+   "category": "phrase",
+   "query": "zero-knowledge encrypted backup",
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+    "8f3abb0d-77ed-4af3-9f4d-ba62cd198886",
+    "7774a16c-1027-4e3b-a21e-67f1f95a4acd",
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+  {
+   "id": "q14",
+   "category": "paraphrase",
+   "query": "the elderly relative who passed while he stayed away",
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+  {
+   "id": "q15",
+   "category": "paraphrase",
+   "query": "a soldier sidelined by illness who refused to quit",
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+  {
+   "id": "q16",
+   "category": "paraphrase",
+   "query": "choosing an uncomfortable fact over a pleasant fiction",
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+   "query": "a tight payload beats a bloated one",
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+  {
+   "id": "q18",
+   "category": "paraphrase",
+   "query": "if you are able and nobody is coming the job is yours",
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+  {
+   "id": "q19",
+   "category": "paraphrase",
+   "query": "learning is the wealth creditors cannot seize",
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+  {
+   "id": "q20",
+   "category": "paraphrase",
+   "query": "reliability proven by track record not assertion",
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+   "query": "boundaries that enable instead of confine",
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+  {
+   "id": "q22",
+   "category": "paraphrase",
+   "query": "what shifts tells you where to cut a system apart",
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+  {
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+   "query": "a mind that compounds instead of resetting each day",
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+  {
+   "id": "q24",
+   "category": "paraphrase",
+   "query": "loved for the unedited self and not the polished exterior",
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+  {
+   "id": "q25",
+   "category": "paraphrase",
+   "query": "cheerfulness you arrive at instead of assuming",
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+  {
+   "id": "q26",
+   "category": "paraphrase",
+   "query": "a childhood offering no solid foundation to inherit",
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+  {
+   "id": "q27",
+   "category": "associative",
+   "query": "Grandma Lucas stroke February 2006 goodbye window",
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+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
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+  {
+   "id": "q28",
+   "category": "associative",
+   "query": "Marines hernia sepsis medical ward",
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+   "n_returned": 10,
+   "latency_ms": 536.9,
+   "error": null,
+   "hit@5": 1.0,
+   "recall@5": 0.07692307692307693,
+   "recall@10": 0.3076923076923077,
+   "precision@5": 0.2,
+   "mrr@10": 0.25
+  },
+  {
+   "id": "q29",
+   "category": "associative",
+   "query": "Sarah Bishop Dyer trailer performance",
+   "returned": [
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "766de879-f9d0-4a07-b6df-b43ee13763d8",
+    "015644f5-8194-4af0-800d-dd4a0cd71396",
+    "tag-trailer-park-paladins",
+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40",
+    "project-trailer-park-paladins",
+    "kn-78db5396-3dbc-4481-bfc7-e4e1422feb1c"
+   ],
+   "n_returned": 10,
+   "latency_ms": 562.4,
+   "error": null,
+   "hit@5": 1.0,
+   "recall@5": 0.18181818181818182,
+   "recall@10": 0.45454545454545453,
+   "precision@5": 0.4,
+   "mrr@10": 0.5
+  },
+  {
+   "id": "q30",
+   "category": "associative",
+   "query": "Swarm Architecture containment lateral worker",
+   "returned": [
+    "bl-0fac287f-f4c0-4f15-bc4d-ff7f8a7af3ae",
+    "bl-9bde67c1-f0ba-4c3a-8fe5-de0deee0ce43",
+    "bl-2515d870-e35e-443b-ba20-5150bbc73fed",
+    "kn-a5b3d0ac-f6a1-49a4-aebb-b8b4cd67fe83",
+    "kn-b36902cc-0b05-44ba-9aa7-800e5dea9ca9",
+    "bl-bea7473c-c687-414c-9c0b-00c509a616c1",
+    "bl-fc6fcb0b-9e4b-40bf-8e88-dbfe4e27c31a",
+    "kn-6f248a50-355b-47bb-aec8-e0e646a9b077",
+    "kn-6061318f-046b-4935-907d-8eafdce14930",
+    "mem-ab34c2f7-3243-424b-affa-25555f6cf9cc"
+   ],
+   "n_returned": 10,
+   "latency_ms": 556.6,
+   "error": null,
+   "hit@5": 0.0,
+   "recall@5": 0.0,
+   "recall@10": 0.0,
+   "precision@5": 0.0,
+   "mrr@10": 0.0
+  },
+  {
+   "id": "q31",
+   "category": "associative",
+   "query": "hope won inside the narrative preface",
+   "returned": [
+    "kn-e0423482-cfa5-4796-8689-8495c93b66bc",
+    "knw-e94982a2-358d-4f2f-af31-8ee0fcec07c6",
+    "bl-2b00aeb0-c0fa-4a9f-8f30-4207e98b3d52",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "kn-5b606390-a52d-4ca2-8e0e-eba141d13440",
+    "knw-4aebd815-4eaf-49d7-954b-03595f3d48be",
+    "knw-723551f5-1950-42a3-8b89-b6a06913cef0",
+    "tag-hope",
+    "knw-d357b6bb-ad8a-4791-b516-426aea45fa5b",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e"
+   ],
+   "n_returned": 10,
+   "latency_ms": 542.6,
+   "error": null,
+   "hit@5": 1.0,
+   "recall@5": 0.09090909090909091,
+   "recall@10": 0.18181818181818182,
+   "precision@5": 0.2,
+   "mrr@10": 0.25
+  },
+  {
+   "id": "q32",
+   "category": "associative",
+   "query": "man of the house six years old expectation",
+   "returned": [
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "knw-528dbc37-eabc-4b75-a7a5-65bf38d6018a",
+    "knw-d357b6bb-ad8a-4791-b516-426aea45fa5b",
+    "knw-473f3f24-20f6-4f39-8589-3709538eb6ac",
+    "mem-a0b7cfda-bc9e-4f40-b9a9-1722cf3f8263",
+    "knw-7902acca-604e-409b-8faf-ad85424211d0",
+    "knw-35940684-abc4-42f0-b942-818f66b1f69a",
+    "4f698ae6-c40e-464e-9798-50350991a188",
+    "719aa819-00a9-4f4b-a857-4f9fe5ad44d7",
+    "kn-6061318f-046b-4935-907d-8eafdce14930"
+   ],
+   "n_returned": 10,
+   "latency_ms": 683.5,
+   "error": null,
+   "hit@5": 0.0,
+   "recall@5": 0.0,
+   "recall@10": 0.0,
+   "precision@5": 0.0,
+   "mrr@10": 0.0
+  },
+  {
+   "id": "q33",
+   "category": "nonsense",
+   "query": "zqxjvw plimforth grebulon",
+   "returned": [],
+   "n_returned": 0,
+   "latency_ms": 350.4,
+   "error": null,
+   "clean": true,
+   "false_positives": 0
+  },
+  {
+   "id": "q34",
+   "category": "nonsense",
+   "query": "flarnbistle quommetry",
+   "returned": [],
+   "n_returned": 0,
+   "latency_ms": 258.4,
+   "error": null,
+   "clean": true,
+   "false_positives": 0
+  },
+  {
+   "id": "q35",
+   "category": "nonsense",
+   "query": "xxqzzt vurblenacht throom",
+   "returned": [],
+   "n_returned": 0,
+   "latency_ms": 348.4,
+   "error": null,
+   "clean": true,
+   "false_positives": 0
+  },
+  {
+   "id": "q36",
+   "category": "superseded",
+   "query": "is the self-improvement architecture called DARMA or DHARMA",
+   "returned": [
+    "mem-f3b37427-b7d1-4f7e-b32c-0241a20ce8da",
+    "mem-80d7416b-20e9-48a0-b176-b215527e2f56",
+    "tag-__darma____cgi____patents____self-improvement____character-preservation____autonomous____architecture__",
+    "kn-b7e98d63-8b83-4911-b4d0-990602a7f575",
+    "tag-__darma____cgi____patents____self-improvement____character-preservation____autonomous____kotlin____architecture__",
+    "knw-e047bb42-dc5b-4383-9e88-e508dc03abe3",
+    "mem-c17aefb1-38b5-4ced-af50-fe524127e1a4",
+    "bl-5b17bd3b-0c41-46cb-a710-6fa4429692ff",
+    "bl-145a0985-2382-400f-a7c5-c335c5e30a72",
+    "mem-82b93b21-a865-410f-9ec1-fc54121d9bb5"
+   ],
+   "n_returned": 10,
+   "latency_ms": 664.5,
+   "error": null,
+   "hit@5": 1.0,
+   "recall@5": 1.0,
+   "recall@10": 1.0,
+   "precision@5": 0.2,
+   "mrr@10": 0.5,
+   "outranks": true,
+   "rank_correct": 2,
+   "rank_stale": 8
+  },
+  {
+   "id": "q37",
+   "category": "superseded",
+   "query": "how many provisional patents does Will actually have",
+   "returned": [
+    "mem-6f0b2b45-90c1-4356-ac01-3daac05b09c8",
+    "12082f7e-e320-438b-bd65-083d8259748f",
+    "015644f5-8194-4af0-800d-dd4a0cd71396",
+    "13705072-4515-4124-963d-083af490494f",
+    "527ecb25-2587-47eb-8269-73be2431abd4",
+    "6de314bf-5c4c-4cfc-871f-fa2e422d45e6",
+    "a1000001-0000-0000-0000-000000000002",
+    "3cf706a1-3825-45d8-b0a9-06cae6cdf5b8",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "de3b6428-b76c-4c44-90e0-bf1dd6998027"
+   ],
+   "n_returned": 10,
+   "latency_ms": 747.3,
+   "error": null,
+   "hit@5": 0.0,
+   "recall@5": 0.0,
+   "recall@10": 1.0,
+   "precision@5": 0.0,
+   "mrr@10": 0.125,
+   "outranks": true,
+   "rank_correct": 8,
+   "rank_stale": null
+  },
+  {
+   "id": "q38",
+   "category": "superseded",
+   "query": "is MCP still the live integration layer",
+   "returned": [
+    "5fcba804-eb5b-48ec-82da-146b1c6bb50d",
+    "bl-7328cbe3-0200-43c2-88e7-0a164e15fca4",
+    "bl-c8c19362-430b-4817-9cf4-9e85e0099c64",
+    "bl-c5c6571e-118f-47c7-8cbb-3ed0ebf64a51",
+    "mem-101e81b4-8097-4749-8d8d-7bb66de34517",
+    "ctx-3a55",
+    "86228228-7adf-41fb-b4c4-9ceea87953ae",
+    "4509ed62-9fb2-48b8-9038-ac569fca9604",
+    "bl-4f7b651b-6b33-449c-8a3b-cfce12ce984b",
+    "mem-3a2cf162-d93b-4f29-86f2-5066fb7fe1f5"
+   ],
+   "n_returned": 10,
+   "latency_ms": 504.2,
+   "error": null,
+   "hit@5": 0.0,
+   "recall@5": 0.0,
+   "recall@10": 0.0,
+   "precision@5": 0.0,
+   "mrr@10": 0.0,
+   "outranks": false,
+   "rank_correct": null,
+   "rank_stale": 5
+  }
+ ]
+}

tools/retrieval-eval/run_comparison.sh

@@ -0,0 +1,98 @@
+#!/usr/bin/env bash
+# run_comparison.sh — the whole harness, end to end, from two git refs.
+#
+# Builds a soul from each ref, boots each on its own throwaway port with its own
+# throwaway HOME and its own disposable copy of the corpus, runs the gold set N
+# times per ref, and prints the comparison with its noise threshold.
+#
+# SAFETY: never touches ~/.neuron, /Applications/Neuron*, ~/neuron-dev-stack, or
+# any running service. Sources are exported with `git archive` into a scratch
+# dir, so no worktree or branch state is mutated either. Ports are checked
+# against the live set before anything boots. Every soul this script starts is
+# killed and confirmed dead by run_eval.py; the sweep at the end is a backstop.
+#
+# usage:
+#   run_comparison.sh [--baseline main] [--candidate feat/recall-through-activation]
+#                     [--repeats 3] [--corpus <snapshot.json>] [--repo <path>]
+set -euo pipefail
+
+BASELINE="main"
+CANDIDATE="feat/recall-through-activation"
+REPEATS=3
+CORPUS="$HOME/neuron-memory-backups/snapshot-pre-repair-20260806.json"
+REPO="$HOME/Development/neuron"
+BASE_PORT=7893
+
+while [ $# -gt 0 ]; do
+  case "$1" in
+    --baseline)  BASELINE="$2"; shift 2 ;;
+    --candidate) CANDIDATE="$2"; shift 2 ;;
+    --repeats)   REPEATS="$2"; shift 2 ;;
+    --corpus)    CORPUS="$2"; shift 2 ;;
+    --repo)      REPO="$2"; shift 2 ;;
+    *) echo "unknown arg: $1" >&2; exit 2 ;;
+  esac
+done
+
+HERE="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+WORK="$(mktemp -d "${TMPDIR:-/tmp}/retrieval-eval.XXXXXX")"
+trap 'rm -rf "$WORK"' EXIT
+
+[ -f "$CORPUS" ] || { echo "no corpus at $CORPUS" >&2; exit 2; }
+echo "corpus: $CORPUS ($(du -h "$CORPUS" | cut -f1))"
+
+slug() { printf '%s' "$1" | tr '/' '-'; }
+
+build_ref() {   # ref -> binary path
+  local ref="$1" out="$WORK/soul-$(slug "$1")"
+  local src="$WORK/src-$(slug "$1")"
+  mkdir -p "$src"
+  git -C "$REPO" archive "$ref" | tar -x -C "$src"
+  "$HERE/build-soul.sh" "$src" "$out" >&2
+  printf '%s' "$out"
+}
+
+echo "== building $BASELINE =="
+BIN_A="$(build_ref "$BASELINE")"
+echo "== building $CANDIDATE =="
+BIN_B="$(build_ref "$CANDIDATE")"
+
+echo "== validating the gold set against this corpus =="
+python3 "$HERE/build_gold_set.py" "$CORPUS" --check
+
+port=$BASE_PORT
+run_one() { # binary label out
+  echo "== $2 =="
+  python3 "$HERE/run_eval.py" --soul "$1" --corpus "$CORPUS" --label "$2" \
+      --port "$port" --out "$3"
+  port=$((port + 1))
+}
+
+A_MAIN="$WORK/results-a-1.json"; B_MAIN="$WORK/results-b-1.json"
+A_REP=(); B_REP=()
+for i in $(seq 1 "$REPEATS"); do
+  a="$WORK/results-a-$i.json"; b="$WORK/results-b-$i.json"
+  run_one "$BIN_A" "$(slug "$BASELINE")-r$i" "$a"
+  run_one "$BIN_B" "$(slug "$CANDIDATE")-r$i" "$b"
+  [ "$i" -gt 1 ] && { A_REP+=("$a"); B_REP+=("$b"); }
+done
+
+cp "$A_MAIN" "$HERE/results-$(slug "$BASELINE").json"
+cp "$B_MAIN" "$HERE/results-$(slug "$CANDIDATE").json"
+
+echo
+python3 "$HERE/compare.py" \
+  --baseline "$A_MAIN" --candidate "$B_MAIN" \
+  ${A_REP[@]+--repeats-baseline "${A_REP[@]}"} \
+  ${B_REP[@]+--repeats-candidate "${B_REP[@]}"} \
+  --out "$HERE/comparison-$(slug "$BASELINE")-vs-$(slug "$CANDIDATE").json"
+
+# Backstop: run_eval.py kills and confirms its own child, but a crashed run
+# could leak one. Leaving a soul running is how the live engine got squeezed.
+STRAY=$(pgrep -f "$WORK/soul-" || true)
+if [ -n "$STRAY" ]; then
+  echo "!! stray eval souls, killing: $STRAY" >&2
+  kill -9 $STRAY 2>/dev/null || true
+fi
+pgrep -f "$WORK/soul-" >/dev/null && { echo "!! STILL RUNNING" >&2; exit 5; }
+echo "process check: no eval souls running"

tools/retrieval-eval/run_eval.py

@@ -0,0 +1,398 @@
+#!/usr/bin/env python3
+"""
+run_eval.py — measure one soul build's retrieval against the gold set.
+
+WHAT IT MEASURES, AND WHY IT BOOTS A REAL SOUL
+    The point is Will's designed retrieval — spreading activation over the
+    weighted directed graph with four-factor multiplicative scoring — not a
+    Python re-implementation of it. A re-implementation would measure my
+    reading of the design; booting the compiled binary measures the design. So
+    this harness compiles the actual `soul.el` amalgam (build-soul.sh) and asks
+    it over HTTP, exactly as the MCP wrapper and the app do.
+
+SAFETY — read this before changing anything here
+    * Boots on a THROWAWAY port with a THROWAWAY $HOME and a THROWAWAY COPY of
+      the corpus. Refuses to use 7770 / 8742 / 7779 / 17779 / 7771.
+    * ENGRAM_URL / SOUL_ENGRAM_URL are UNSET and SOUL_ISE_URL is pinned to a
+      dead port. This is not belt-and-braces: the periodic engram sync resolves
+      its source as env(SOUL_ISE_URL) -> state -> DEFAULT http://localhost:8742,
+      so leaving it unset makes an "isolated" run silently pull the operator's
+      LIVE brain. (Learned the hard way on 2026-08-03; see the same note in
+      scripts/verify-soul-contract.sh.)
+    * Every process this file starts is tracked and killed in a finally block,
+      then CONFIRMED dead by pid probe, and the confirmation is written into the
+      results file. A run that cannot confirm its child is dead exits non-zero.
+    * Activation is a STATEFUL read by design (patent claim 29: traversal
+      updates last-activation and increments activation counts). The corpus copy
+      is therefore per-run and disposable, and every run starts from a byte-
+      identical copy so two configurations see the same starting graph.
+
+usage:
+  python3 run_eval.py --soul <binary> --corpus <snapshot.json> --label main \
+      [--port 7893] [--gold gold_set.json] [--limit 10] [--out results-main.json]
+"""
+import argparse
+import json
+import os
+import shutil
+import signal
+import subprocess
+import sys
+import tempfile
+import time
+import urllib.error
+import urllib.parse
+import urllib.request
+
+HERE = os.path.dirname(os.path.abspath(__file__))
+FORBIDDEN_PORTS = {7770, 8742, 7779, 17779, 7771, 8080}
+
+
+# ─────────────────────────────────────────────────────────────────────────────
+# metrics
+# ─────────────────────────────────────────────────────────────────────────────
+def recall_at_k(returned, relevant, k):
+    if not relevant:
+        return None
+    return len(set(returned[:k]) & set(relevant)) / len(relevant)
+
+
+def hit_at_k(returned, relevant, k):
+    if not relevant:
+        return None
+    return 1.0 if set(returned[:k]) & set(relevant) else 0.0
+
+
+def precision_at_k(returned, relevant, k):
+    """Fixed denominator k, as in docs/research/graphrag_eval/score.py.
+
+    Fixed denominator penalises an empty result and a page of junk equally,
+    which is what we want: a retriever that returns nothing is not 'precise'.
+    """
+    if not relevant:
+        return None
+    return len(set(returned[:k]) & set(relevant)) / k
+
+
+def mrr(returned, relevant, k):
+    if not relevant:
+        return None
+    rel = set(relevant)
+    for i, nid in enumerate(returned[:k], start=1):
+        if nid in rel:
+            return 1.0 / i
+    return 0.0
+
+
+def mean(vals):
+    vals = [v for v in vals if v is not None]
+    return sum(vals) / len(vals) if vals else 0.0
+
+
+def pct(vals):
+    return f"{100 * mean(vals):.1f}%"
+
+
+# ─────────────────────────────────────────────────────────────────────────────
+# soul lifecycle
+# ─────────────────────────────────────────────────────────────────────────────
+class Soul:
+    def __init__(self, binary, corpus, port, verbose=True):
+        if port in FORBIDDEN_PORTS:
+            raise SystemExit(f"REFUSING: port {port} is a live service port.")
+        self.binary = os.path.abspath(binary)
+        self.corpus = os.path.abspath(corpus)
+        self.port = port
+        self.verbose = verbose
+        self.home = None
+        self.proc = None
+        self.pid = None
+        self.log = None
+        self.confirmed_dead = None
+
+    @property
+    def base(self):
+        return f"http://127.0.0.1:{self.port}"
+
+    def start(self, boot_timeout=180):
+        self.home = tempfile.mkdtemp(prefix="retrieval-eval-home.")
+        snap = os.path.join(self.home, "corpus.json")
+        t0 = time.time()
+        shutil.copyfile(self.corpus, snap)   # per-run disposable copy, never the source
+        self.log = os.path.join(self.home, "soul.log")
+
+        env = {k: v for k, v in os.environ.items()
+               if k not in ("ENGRAM_URL", "ENGRAM_API_KEY", "SOUL_ENGRAM_URL",
+                            "ANTHROPIC_API_KEY", "NEURON_LLM_API_KEY", "SOUL_IDENTITY",
+                            "SOUL_API_KEY")}
+        env.update({
+            "HOME": self.home,
+            "NEURON_PORT": str(self.port),
+            "SOUL_CGI_ID": f"ntn-retrieval-eval-{os.getpid()}",
+            "SOUL_ENGRAM_PATH": snap,
+            "NEURON_API_URL": "http://127.0.0.1:9",   # dead port
+            "SOUL_ISE_URL": "http://127.0.0.1:9",     # dead port — see SAFETY above
+            # Park the background loops for an hour so heartbeat/consolidation
+            # cannot mutate the graph between queries and make runs unrepeatable.
+            "SOUL_TICK_MS": "3600000",
+            "SOUL_HEARTBEAT_MS": "3600000",
+            "SOUL_REFRESH_MS": "3600000",
+        })
+        with open(self.log, "wb") as lf:
+            self.proc = subprocess.Popen([self.binary], env=env, stdout=lf, stderr=lf,
+                                         start_new_session=True)
+        self.pid = self.proc.pid
+        if self.verbose:
+            print(f"  booted pid={self.pid} port={self.port} home={self.home}")
+
+        deadline = time.time() + boot_timeout
+        while time.time() < deadline:
+            if self.proc.poll() is not None:
+                raise RuntimeError(f"soul exited during boot: {self._log_tail()}")
+            rss = self._rss_kb()
+            if rss and rss > 6 * 1024 * 1024:
+                self.stop()
+                raise RuntimeError(f"soul RSS {rss}KB > 6GB — aborted")
+            try:
+                with urllib.request.urlopen(f"{self.base}/health", timeout=2) as r:
+                    if r.status == 200:
+                        if self.verbose:
+                            print(f"  healthy in {time.time() - t0:.1f}s, RSS={self._rss_kb()}KB")
+                        return
+            except Exception:
+                pass
+            time.sleep(0.5)
+        self.stop()
+        raise RuntimeError(f"soul never healthy on {self.base}: {self._log_tail()}")
+
+    def _rss_kb(self):
+        try:
+            out = subprocess.run(["ps", "-o", "rss=", "-p", str(self.pid)],
+                                 capture_output=True, text=True, timeout=5).stdout.strip()
+            return int(out) if out else None
+        except Exception:
+            return None
+
+    def _log_tail(self, n=15):
+        try:
+            with open(self.log, encoding="utf-8", errors="replace") as fh:
+                return "\n".join(fh.read().splitlines()[-n:])
+        except Exception:
+            return "(no log)"
+
+    def recall(self, query, limit, timeout=60):
+        url = f"{self.base}/api/neuron/recall?query={urllib.parse.quote(query)}&limit={limit}"
+        t0 = time.perf_counter()
+        try:
+            with urllib.request.urlopen(url, timeout=timeout) as r:
+                raw = r.read().decode("utf-8", "replace")
+            ms = (time.perf_counter() - t0) * 1000
+        except Exception as exc:
+            return [], (time.perf_counter() - t0) * 1000, f"{type(exc).__name__}: {exc}"
+        try:
+            arr = json.loads(raw)
+        except Exception:
+            return [], ms, f"unparseable response ({len(raw)}B)"
+        if not isinstance(arr, list):
+            return [], ms, f"non-array response: {str(arr)[:120]}"
+        ids = [x.get("id") for x in arr if isinstance(x, dict) and x.get("id")]
+        return ids, ms, None
+
+    def stop(self):
+        """Kill and CONFIRM. A test process that outlives its test is a bug."""
+        if self.pid is None:
+            self.confirmed_dead = True
+            return True
+        for sig in (signal.SIGTERM, signal.SIGKILL):
+            try:
+                os.kill(self.pid, sig)
+            except ProcessLookupError:
+                break
+            except Exception:
+                pass
+            for _ in range(20):
+                try:
+                    os.kill(self.pid, 0)
+                except ProcessLookupError:
+                    break
+                time.sleep(0.1)
+            else:
+                continue
+            break
+        try:
+            self.proc.wait(timeout=5)
+        except Exception:
+            pass
+        try:
+            os.kill(self.pid, 0)
+            self.confirmed_dead = False
+        except ProcessLookupError:
+            self.confirmed_dead = True
+        if self.verbose:
+            print(f"  pid {self.pid}: {'CONFIRMED DEAD' if self.confirmed_dead else 'STILL ALIVE'}")
+        if self.home and os.path.isdir(self.home):
+            shutil.rmtree(self.home, ignore_errors=True)
+        return self.confirmed_dead
+
+
+# ─────────────────────────────────────────────────────────────────────────────
+# eval
+# ─────────────────────────────────────────────────────────────────────────────
+def evaluate(soul, gold, limit):
+    rows = []
+    for q in gold["queries"]:
+        ids, ms, err = soul.recall(q["query"], limit)
+        rel = q.get("relevant") or []
+        row = {
+            "id": q["id"],
+            "category": q["category"],
+            "query": q["query"],
+            "returned": ids,
+            "n_returned": len(ids),
+            "latency_ms": round(ms, 1),
+            "error": err,
+        }
+        if q.get("expect_empty"):
+            row["clean"] = (len(ids) == 0)
+            row["false_positives"] = len(ids)
+        else:
+            row["hit@5"] = hit_at_k(ids, rel, 5)
+            row["recall@5"] = recall_at_k(ids, rel, 5)
+            row["recall@10"] = recall_at_k(ids, rel, 10)
+            row["precision@5"] = precision_at_k(ids, rel, 5)
+            row["mrr@10"] = mrr(ids, rel, 10)
+        if q.get("must_outrank"):
+            correct, stale = q["must_outrank"]
+            ic = ids.index(correct) if correct in ids else None
+            istale = ids.index(stale) if stale in ids else None
+            # Correct must be present AND above the stale node. A run that
+            # returns neither is NOT a pass: the corrected fact is what the
+            # user needed.
+            row["outranks"] = (ic is not None) and (istale is None or ic < istale)
+            row["rank_correct"] = None if ic is None else ic + 1
+            row["rank_stale"] = None if istale is None else istale + 1
+        rows.append(row)
+    return rows
+
+
+def aggregate(rows):
+    scored = [r for r in rows if "hit@5" in r]
+    nonsense = [r for r in rows if "clean" in r]
+    outrank = [r for r in rows if "outranks" in r]
+    lat = sorted(r["latency_ms"] for r in rows)
+    agg = {
+        "n_queries": len(rows),
+        "n_scored": len(scored),
+        "hit@5": mean([r["hit@5"] for r in scored]),
+        "recall@5": mean([r["recall@5"] for r in scored]),
+        "recall@10": mean([r["recall@10"] for r in scored]),
+        "precision@5": mean([r["precision@5"] for r in scored]),
+        "mrr@10": mean([r["mrr@10"] for r in scored]),
+        "nonsense_clean": f"{sum(1 for r in nonsense if r['clean'])}/{len(nonsense)}",
+        "superseded_outranks": f"{sum(1 for r in outrank if r['outranks'])}/{len(outrank)}",
+        "latency_ms_p50": lat[len(lat) // 2] if lat else 0,
+        "latency_ms_p95": lat[max(0, int(len(lat) * 0.95) - 1)] if lat else 0,
+        "latency_ms_max": lat[-1] if lat else 0,
+        "errors": sum(1 for r in rows if r["error"]),
+        "by_category": {},
+    }
+    cats = sorted({r["category"] for r in rows})
+    for c in cats:
+        cr = [r for r in rows if r["category"] == c]
+        if c == "nonsense":
+            agg["by_category"][c] = {
+                "n": len(cr),
+                "clean": sum(1 for r in cr if r["clean"]),
+                "avg_false_positives": mean([float(r["false_positives"]) for r in cr]),
+            }
+        else:
+            e = {
+                "n": len(cr),
+                "hit@5": mean([r.get("hit@5") for r in cr]),
+                "recall@5": mean([r.get("recall@5") for r in cr]),
+                "recall@10": mean([r.get("recall@10") for r in cr]),
+                "mrr@10": mean([r.get("mrr@10") for r in cr]),
+            }
+            if c == "superseded":
+                e["outranks"] = sum(1 for r in cr if r.get("outranks"))
+            agg["by_category"][c] = e
+    return agg
+
+
+def print_table(label, agg):
+    print(f"\n=== {label} ===")
+    print(f"  queries {agg['n_queries']} ({agg['n_scored']} scored + "
+          f"{agg['n_queries'] - agg['n_scored']} control) · errors {agg['errors']}")
+    print(f"  {'hit@5':>12} {'recall@5':>10} {'recall@10':>10} {'prec@5':>9} {'MRR@10':>9}")
+    print(f"  {pct([agg['hit@5']]):>12} {pct([agg['recall@5']]):>10} {pct([agg['recall@10']]):>10} "
+          f"{pct([agg['precision@5']]):>9} {agg['mrr@10']:>9.3f}")
+    print(f"  nonsense clean {agg['nonsense_clean']} · superseded outranks {agg['superseded_outranks']}")
+    print(f"  latency ms  p50 {agg['latency_ms_p50']:.0f} · p95 {agg['latency_ms_p95']:.0f} "
+          f"· max {agg['latency_ms_max']:.0f}")
+    print(f"\n  {'category':14} {'n':>3} {'hit@5':>8} {'recall@5':>9} {'recall@10':>10} {'MRR@10':>8}")
+    for c, e in agg["by_category"].items():
+        if c == "nonsense":
+            print(f"  {c:14} {e['n']:>3} {'clean ' + str(e['clean']) + '/' + str(e['n']):>8}"
+                  f"{'':>9} {'':>10} {'avg FP ' + format(e['avg_false_positives'], '.1f'):>8}")
+        else:
+            extra = f"  outranks {e['outranks']}/{e['n']}" if "outranks" in e else ""
+            print(f"  {c:14} {e['n']:>3} {pct([e['hit@5']]):>8} {pct([e['recall@5']]):>9} "
+                  f"{pct([e['recall@10']]):>10} {e['mrr@10']:>8.3f}{extra}")
+
+
+def main():
+    ap = argparse.ArgumentParser()
+    ap.add_argument("--soul", required=True)
+    ap.add_argument("--corpus", required=True)
+    ap.add_argument("--label", required=True)
+    ap.add_argument("--gold", default=os.path.join(HERE, "gold_set.json"))
+    ap.add_argument("--port", type=int, default=7893)
+    ap.add_argument("--limit", type=int, default=10)
+    ap.add_argument("--out", default=None)
+    args = ap.parse_args()
+
+    with open(args.gold, encoding="utf-8") as fh:
+        gold = json.load(fh)
+    print(f"[{args.label}] soul={os.path.basename(args.soul)} "
+          f"corpus={os.path.basename(args.corpus)} gold={len(gold['queries'])}q limit={args.limit}")
+
+    soul = Soul(args.soul, args.corpus, args.port)
+    rows = []
+    started = time.time()
+    try:
+        soul.start()
+        rows = evaluate(soul, gold, args.limit)
+    finally:
+        dead = soul.stop()
+
+    agg = aggregate(rows)
+    print_table(args.label, agg)
+
+    out = args.out or os.path.join(HERE, f"results-{args.label}.json")
+    doc = {
+        "label": args.label,
+        "soul_binary": os.path.abspath(args.soul),
+        "soul_md5": subprocess.run(["md5", "-q", args.soul], capture_output=True,
+                                   text=True).stdout.strip(),
+        "corpus": os.path.abspath(args.corpus),
+        "corpus_nodes": gold.get("corpus_nodes"),
+        "corpus_edges": gold.get("corpus_edges"),
+        "gold_set": os.path.abspath(args.gold),
+        "limit": args.limit,
+        "port": args.port,
+        "wall_clock_s": round(time.time() - started, 1),
+        "child_pid": soul.pid,
+        "child_confirmed_dead": soul.confirmed_dead,
+        "aggregate": agg,
+        "rows": rows,
+    }
+    with open(out, "w", encoding="utf-8") as fh:
+        json.dump(doc, fh, indent=1, ensure_ascii=False)
+    print(f"\nwrote {out}")
+    if not dead:
+        print("FATAL: child process could not be confirmed dead", file=sys.stderr)
+        sys.exit(4)
+
+
+if __name__ == "__main__":
+    main()

tools/retrieval-eval/sim-bm25.py

@@ -0,0 +1,142 @@
+import numpy as np, json, urllib.request, collections, math, re, sys, time
+SP="/private/tmp/claude-501/-Users-timlingo/82369039-a20e-4b5a-8a5e-28234a57b996/scratchpad"
+EV="/Users/timlingo/Development/neuron-technologies/_wt-semseed/tools/retrieval-eval/"
+np.seterr(all='ignore')
+t0=time.time()
+M=np.load(SP+'/emb.npy'); eids=open(SP+'/ids.txt',encoding='utf-8',errors='surrogateescape').read().split('\n')
+eidx={k:i for i,k in enumerate(eids)}
+d=json.load(open('/Users/timlingo/neuron-memory-backups/snapshot-pre-repair-20260806.json',encoding='utf-8',errors='surrogateescape'))
+print("loaded corpus %.1fs"%(time.time()-t0),file=sys.stderr)
+STRUCT={"identity","contains","superseded_by","references","embodies","demonstrated_by","canonical-self","depends_on","currently_holds","activates"}
+adj=collections.defaultdict(list)
+for e in d['edges']:
+    if e.get('relation') not in STRUCT: continue
+    w=float(e.get('weight') or 0.0)
+    adj[e['from_id']].append((e['to_id'],w)); adj[e['to_id']].append((e['from_id'],w))
+nodes=d['nodes']
+N={n['id']:n for n in nodes}
+PRINT=re.compile(r'^[\x20-\x7e]+$')
+ids=[]; hay=[]; dl=[]; sal=[]; addressable=[]
+for n in nodes:
+    i=n.get('id') or ''
+    h=((n.get('content') or '')+'\x00'+(n.get('label') or '')+'\x00'+(n.get('tags') or '')).lower()
+    ids.append(i); hay.append(h); dl.append(len(h)); sal.append(float(n.get('salience') or 0.0))
+    addressable.append(bool(PRINT.match(i)))
+del d
+NN=len(ids); avgdl=sum(dl)/NN
+print("nodes=%d avgdl=%.0f addressable=%d  %.1fs"%(NN,avgdl,sum(addressable),time.time()-t0),file=sys.stderr)
+gold={q['id']:q for q in json.load(open(EV+"gold_set.json"))['queries']}
+LEXMAIN={r['id']:r['returned'] for r in json.load(open(EV+"results-main.json"),) ['rows']} if False else {r['id']:r['returned'] for r in json.load(open(EV+"results-main.json",encoding='utf-8',errors='surrogateescape'))['rows']}
+CACHE={}
+def emb(t):
+    if t in CACHE: return CACHE[t]
+    b=json.dumps({"model":"nomic-embed-text","prompt":t}).encode()
+    r=urllib.request.Request("http://127.0.0.1:11434/api/embeddings",data=b,headers={"Content-Type":"application/json"})
+    v=np.array(json.load(urllib.request.urlopen(r,timeout=60))["embedding"],dtype=np.float32)
+    v=v/(np.linalg.norm(v)+1e-9); CACHE[t]=v; return v
+K1,B=1.2,0.75
+def lexleg(query, mode, guard, lim=10):
+    toks=[]
+    for w in query.split():
+        wl=w.lower()
+        if wl not in toks: toks.append(wl)
+    nt=len(toks)
+    masks=[]; df=[0]*nt
+    for i in range(NN):
+        if guard and not addressable[i]: continue
+        h=hay[i]; m=0; sc=0
+        for t in range(nt):
+            if toks[t] in h: m|=(1<<t); sc+=1; df[t]+=1
+        if sc: masks.append((i,m,sc))
+    if mode=='tokcount':
+        masks.sort(key=lambda x:(-x[2], -sal[x[0]]))
+        return [ids[i] for i,m,sc in masks[:lim]]
+    idf=[math.log(1.0+(NN-df[t]+0.5)/(df[t]+0.5)) for t in range(nt)]
+    scored=[]
+    for i,m,sc in masks:
+        norm=1.0-B+B*dl[i]/avgdl
+        s=0.0
+        for t in range(nt):
+            if m&(1<<t): s+=idf[t]*(K1+1.0)/(1.0+K1*norm)
+        scored.append((s,i))
+    scored.sort(key=lambda x:(-x[0], -sal[x[1]]))
+    return [ids[i] for s,i in scored[:lim]]
+FIRE=0.02; DECAY=0.7; DEPTH=2; SEED_MIN=0.60; ASSOC_MAX=64
+def assoc(seeds, s):
+    act={x:1.0 for x in seeds}; seen={x:2 for x in seeds}
+    Q=[(x,0) for x in seeds]; h=0
+    while h<len(Q):
+        cur,hop=Q[h]; h+=1
+        if hop>=DEPTH: continue
+        p=act[cur]
+        for oid,w in adj.get(cur,()):
+            n=N.get(oid)
+            if not n or n.get('node_type') in ('Tag','InternalStateEvent'): continue
+            na=p*w*DECAY*float(n.get('salience') or 0.0)
+            if na<FIRE: continue
+            if oid in seen and na<=act.get(oid,0): continue
+            act[oid]=na
+            if oid not in seen: seen[oid]=1
+            Q.append((oid,hop+1))
+    out=[]
+    for k,v in seen.items():
+        if v!=1 or k not in eidx: continue
+        c=float(s[eidx[k]])
+        if c<=0: continue
+        out.append((c,k))
+    out.sort(reverse=True)
+    return [k for c,k in out[:ASSOC_MAX]]
+def inter3(L,S,A,lim=10):
+    out=[]; li=si=ai=0
+    while len(out)<lim and (li<len(L) or si<len(S) or ai<len(A)):
+        if li<len(L):
+            if L[li] not in out: out.append(L[li])
+            li+=1
+        if len(out)>=lim: break
+        if si<len(S):
+            if S[si] not in out: out.append(S[si])
+            si+=1
+        if len(out)>=lim: break
+        if ai<len(A):
+            if A[ai] not in out: out.append(A[ai])
+            ai+=1
+    return out
+def run(mode, guard, use_main_lex=False):
+    res={}; legs={}
+    for qid,q in gold.items():
+        v=emb(q['query']); s=M@v; s[~np.isfinite(s)]=-1
+        L = LEXMAIN[qid][:10] if use_main_lex else lexleg(q['query'], mode, guard)
+        ordr=np.argsort(-s)
+        S=[eids[j] for j in ordr[:10] if s[j]>SEED_MIN]
+        if guard: S=[x for x in S if PRINT.match(x or '')]
+        seeds=[x for x in L[:3] if x in N]
+        seeds=seeds+[eids[j] for j in ordr[:8] if eids[j] in N and eids[j] not in seeds and (not guard or PRINT.match(eids[j] or ''))]
+        A=assoc(seeds,s) if seeds else []
+        if guard: A=[x for x in A if PRINT.match(x or '')]
+        res[qid]=inter3(L,S,A); legs[qid]=(L,S,A)
+    return res,legs
+def score(res,label,verbose=False):
+    det={}
+    for qid,q in gold.items():
+        out=res[qid][:5]
+        if q['category']=='nonsense': ok=(len(res[qid])==0)
+        elif q['category']=='superseded':
+            must=q.get('must_outrank') or {}; ok=False
+            for good,bad in (must.items() if isinstance(must,dict) else []):
+                ok = good in res[qid] and (bad not in res[qid] or res[qid].index(good)<res[qid].index(bad))
+            if not must: ok=any(r in out for r in q['relevant'])
+        else: ok=any(r in out for r in q['relevant'])
+        det[qid]=ok
+    print("%-28s outcome-true=%d/38"%(label,sum(det.values())))
+    return det
+if __name__=="__main__":
+    base,_=run('tokcount',False,use_main_lex=True); b=score(base,'BASELINE semseed(real lex)')
+    variants=[('tokcount',False,'replica: tokcount,noguard'),
+              ('tokcount',True ,'A: tokcount + idguard'),
+              ('bm25',    False,'B: bm25 only'),
+              ('bm25',    True ,'C: bm25 + idguard')]
+    dets={}
+    for m,g,lab in variants:
+        r,_=run(m,g); dets[lab]=score(r,lab)
+        dd=[q for q in gold if dets[lab][q]!=b[q]]
+        print("     vs BASELINE moved=%d gains=%s losses=%s"%(len(dd),[q for q in dd if dets[lab][q]],[q for q in dd if not dets[lab][q]]))

tools/retrieval-eval/wb2.py

@@ -0,0 +1,92 @@
+import json,sys,pickle,numpy as np
+sys.path.insert(0,'.')
+from legs import *
+GP='/Users/timlingo/Development/neuron-technologies/_wt-bm25lex/tools/retrieval-eval/'
+G=json.load(open(GP+'gold_set.json'))
+def wstart(s,tok):
+    i=s.find(tok)
+    while i!=-1:
+        if i==0 or not s[i-1].isalnum(): return True
+        i=s.find(tok,i+1)
+    return False
+def legs4(query, wordstart=False, unfloor=False):
+    toks=tokenize(query); lt=[t.lower() for t in toks]
+    hit_idx=[];hit_mask=[];df=[0]*len(toks)
+    for i in range(N):
+        if not OK[i]: continue
+        s=LOW[i];m=0
+        for t,tok in enumerate(lt):
+            if tok in s and (not wordstart or wstart(s,tok)): m|=(1<<t)
+        if m:
+            hit_idx.append(i);hit_mask.append(m)
+            for t in range(len(toks)):
+                if m>>t&1: df[t]+=1
+    dl_n=int(OK.sum());avgdl=float(DL[OK].sum()/max(dl_n,1))
+    idf=[math.log(1.0+((dl_n-d+0.5)/(d+0.5))) for d in df]
+    L=[]
+    for j,i in enumerate(hit_idx):
+        norm=1.0-B+B*(DL[i]/avgdl);w=0.0
+        for t in range(len(toks)):
+            if hit_mask[j]>>t&1: w+=idf[t]*(K1+1.0)/(1.0+K1*norm)
+        L.append((i,w,SAL[i]))
+    L.sort(key=lambda x:(-x[1],-x[2]))
+    if not L: return [],[],[]
+    qv=qemb(query);cos=En@qv;cos=np.where(HAVE&OK,cos,-2.0)
+    order=np.argsort(-cos)[:600]
+    Sl=[int(i) for i in order if cos[i]>(0.0 if unfloor else SEED_MIN)]
+    semseed=[int(i) for i in order[:SEED_K] if cos[i]>0.0]
+    act={};seen={};qq=[]
+    for i,_,_ in L[:ASSOC_SEEDS]:
+        act[i]=1.0;seen[i]=2;qq.append((i,0))
+    for i in semseed:
+        if i in seen: continue
+        act[i]=1.0;seen[i]=2;qq.append((i,0))
+    qh=0
+    while qh<len(qq):
+        cur,h=qq[qh];qh+=1
+        if h>=DEPTH: continue
+        parent=act[cur]
+        for e,oi in ADJ_F[cur]+ADJ_T[cur]:
+            if e['rel'] not in STRUCT or EXCL[oi]: continue
+            na=parent*e['w']*DECAY*SAL[oi]
+            if na<FIRE: continue
+            if seen.get(oi) and na<=act.get(oi,0): continue
+            act[oi]=na
+            if not seen.get(oi): seen[oi]=1
+            if len(qq)<AMAX*4: qq.append((oi,h+1))
+    A=sorted([(i,float(cos[i])) for i,st in seen.items() if st==1 and OK[i] and HAVE[i] and cos[i]>0.0],key=lambda x:-x[1])[:AMAX]
+    return [i for i,_,_ in L],Sl,[i for i,_ in A]
+def merge(L,S,A,lim=10):
+    out=[];li=si=ai=0
+    while len(out)<lim and (li<len(L) or si<len(S) or ai<len(A)):
+        if li<len(L):
+            if L[li] not in out: out.append(L[li])
+            li+=1
+        if len(out)>=lim: break
+        if si<len(S):
+            if S[si] not in out: out.append(S[si])
+            si+=1
+        if len(out)>=lim: break
+        if ai<len(A):
+            if A[ai] not in out: out.append(A[ai])
+            ai+=1
+    return out
+def outcome(q,ids):
+    c=q['category']
+    if c=='nonsense': return len(ids)==0
+    if c=='superseded':
+        a,b=q['must_outrank']
+        if a not in ids: return False
+        if b not in ids: return True
+        return ids.index(a)<ids.index(b)
+    return any(x in ids[:5] for x in q['relevant'])
+def run(**kw):
+    return {q['id']:outcome(q,[NODES[i]['id'] for i in merge(*legs4(q['query'],**kw),10)]) for q in G['queries']}
+base=run()
+print("baseline",sum(base.values()),"misses",[k for k,v in base.items() if not v])
+for name,kw in [('wordstart',dict(wordstart=True)),
+                ('unfloor',dict(unfloor=True)),
+                ('wordstart+unfloor',dict(wordstart=True,unfloor=True))]:
+    r=run(**kw)
+    g=sorted(k for k in base if r[k] and not base[k]);l=sorted(k for k in base if base[k] and not r[k])
+    print("%-20s net=%+d gains=%s losses=%s"%(name,len(g)-len(l),g,l))

tools/retrieval-eval/zprobe.py

@@ -0,0 +1,31 @@
+import numpy as np, json, urllib.request
+SP="/private/tmp/claude-501/-Users-timlingo/82369039-a20e-4b5a-8a5e-28234a57b996/scratchpad"
+M=np.load(SP+'/emb.npy'); ids=open(SP+'/ids.txt',encoding='utf-8',errors='surrogateescape').read().split('\n')
+np.seterr(all='ignore')
+bad=~np.isfinite(M).all(axis=1)
+M[bad]=0.0
+print("non-finite rows zeroed:",int(bad.sum()))
+idx={k:i for i,k in enumerate(ids)}
+gold=json.load(open("/Users/timlingo/Development/neuron-technologies/_wt-assoc-leg/tools/retrieval-eval/gold_set.json"))['queries']
+def emb(t):
+    b=json.dumps({"model":"nomic-embed-text","prompt":t}).encode()
+    r=urllib.request.Request("http://127.0.0.1:11434/api/embeddings",data=b,headers={"Content-Type":"application/json"})
+    v=np.array(json.load(urllib.request.urlopen(r,timeout=60))["embedding"],dtype=np.float32)
+    return v/(np.linalg.norm(v)+1e-9)
+out={}
+for q in gold:
+    v=emb(q['query']); s=M@v
+    s=s[np.isfinite(s)]
+    mu=float(s.mean()); sd=float(s.std())
+    top=np.sort(s)[::-1][:10]
+    z=[(float(t)-mu)/sd for t in top]
+    grank=[]
+    for rel in q['relevant']:
+        if rel in idx:
+            j=idx[rel]; grank.append((int((M@v > (M@v)[j]).sum())+1, round(float((M@v)[j]),3)))
+    grank.sort()
+    out[q['id']]=dict(cat=q['category'],mu=round(mu,3),sd=round(sd,4),top1=round(float(top[0]),3),
+                      z1=round(z[0],2),z3=round(z[2],2),z5=round(z[4],2),gold=grank[:1])
+    print("%s %-11s mu=%.3f sd=%.4f top1=%.3f z1=%5.2f z3=%5.2f z5=%5.2f gold=%s"%(
+        q['id'],q['category'],mu,sd,top[0],z[0],z[2],z[4],grank[:1]))
+json.dump(out,open(SP+'/zprobe.json','w'),indent=1)

vendor/el-runtime/v1.0.0-20260501/el_runtime.c

@@ -6099,6 +6099,12 @@ static void engram_bll_parse_access(EngramNode* nn, const char* s) {
  * propagation loop in engram_activate. 0.25 damps semantically unrelated
  * branches ~4x without severing them. Unembedded targets are ungated. */
 #define ENGRAM_QGATE_FLOOR             0.25
+/* The read-path semantic leg (engram claim 24) reuses ENGRAM_EMBED_SEED_MIN
+ * above as its admission floor: a node joins the embedding ranking only if its
+ * query cosine clears the same bar that lets it join the seed set. No new
+ * tuning constant is introduced, and the floor is load-bearing rather than
+ * cosmetic — it is what keeps a query with no real match (the gold set's
+ * nonsense controls) from being answered with its nearest neighbours. */
 #define ENGRAM_EMBED_MAX_CHARS         2000
 #define ENGRAM_EMBED_TIMEOUT_MS        4000L
 #define ENGRAM_EMBED_BREAKER_LIMIT     3
@@ -7169,6 +7175,12 @@ void engram_forget(el_val_t node_id) {
     if (idx < 0) return;
     /* Free node strings */
     EngramNode* n = &g->nodes[idx];
+    if (getenv("EG_DIAG")) {
+        fprintf(stderr, "[EG_DIAG] FORGET id=%s type=%s layer=%u label=%s\n",
+                sid, n->node_type ? n->node_type : "?", n->layer_id,
+                n->label ? n->label : "?");
+        fflush(stderr);
+    }
     free(n->id); free(n->content); free(n->node_type); free(n->label);
     free(n->tier); free(n->tags); free(n->metadata);
     free(n->emb);
@@ -7264,6 +7276,8 @@ el_val_t engram_prune_telemetry(el_val_t older_than_ms) {
         }
     }
     g->node_count = w;
+    if (getenv("EG_DIAG"))
+        fprintf(stderr, "[EG_DIAG] PRUNE_TELEMETRY removed=%lld\n", (long long)removed);
     if (removed == 0) { free(removed_ids); return 0; }
 
     /* Removed-id hash set (open addressing, power-of-two >= 2*removed). */
@@ -7321,6 +7335,39 @@ static int istr_contains(const char* hay, const char* needle) {
     return 0;
 }
 
+/* Word-START-anchored variant of istr_contains.
+ *
+ * WHY. The retrieval match primitive is a raw substring test, so a query token
+ * matches ANYWHERE inside a corpus word: "throom" matches "bathroom", "cat"
+ * matches "concatenate". Measured on this corpus over the 38-query gold set,
+ * that is not a rare accident — it is the bulk of some queries' candidate
+ * sets. q28's lexical leg is 36,954 records of which only 13 contain a query
+ * token at a word start (99.96% mid-word noise); six other queries carry
+ * ~20,500 mid-word-only records each; and the nonsense control q35
+ * ("xxqzzt vurblenacht throom") returns 7 records ALL of which match only
+ * mid-word, which is the entire reason that control has been dirty since main.
+ *
+ * WHAT CHANGES. A token must begin at a word boundary — the preceding
+ * character is not alphanumeric. Suffixes are still matched ("value" still
+ * hits "values", "unjailbreakable" still hits "unjailbreakables"), so this is
+ * strictly a prefix anchor, not whole-word equality; whole-word equality would
+ * break the morphological matching the phrase category depends on.
+ *
+ * PROVENANCE, stated honestly: this restores no engram claim. Will's design
+ * has no lexical leg at all (05-detailed-description l.64 takes "one or more
+ * seed node UUIDs representing the current active context" as its input), so
+ * the lexical leg is the seed-finding step that feeds the designed mechanism.
+ * Cleaner seeds serve that mechanism; they do not replace it. */
+static int istr_contains_wordstart(const char* hay, const char* needle) {
+    if (!hay || !needle || !*needle) return 0;
+    size_t nl = strlen(needle);
+    for (const char* p = hay; *p; p++) {
+        if (p != hay && isalnum((unsigned char)p[-1])) continue;
+        if (strncasecmp(p, needle, nl) == 0) return 1;
+    }
+    return 0;
+}
+
 /* ── Tokenized query matching ───────────────────────────────────────────
  * The engram query surface (search / activate / goal-bias) historically
  * matched the ENTIRE raw query string as a single case-insensitive
@@ -7373,17 +7420,81 @@ static int engram_node_match_score(const EngramNode* n,
                                    char toks[][ENGRAM_QTOK_LEN], int ntok) {
     int score = 0;
     for (int t = 0; t < ntok; t++) {
-        if (istr_contains(n->content, toks[t]) ||
-            istr_contains(n->label,   toks[t]) ||
-            istr_contains(n->tags,    toks[t]))
+        if (istr_contains_wordstart(n->content, toks[t]) ||
+            istr_contains_wordstart(n->label,   toks[t]) ||
+            istr_contains_wordstart(n->tags,    toks[t]))
             score++;
     }
     return score;
 }
 
+/* Same match test as engram_node_match_score, but returns the SET of matched
+ * query tokens as a bitmask instead of only their count. ENGRAM_MAX_QTOKENS is
+ * 32, so one uint32 covers every token the tokenizer can produce. The mask is
+ * what lets the caller accumulate a per-token document frequency in the SAME
+ * pass that finds the hits — no second scan of the corpus. */
+static uint32_t engram_node_match_mask(const EngramNode* n,
+                                       char toks[][ENGRAM_QTOK_LEN], int ntok) {
+    uint32_t m = 0;
+    for (int t = 0; t < ntok && t < 32; t++) {
+        if (istr_contains_wordstart(n->content, toks[t]) ||
+            istr_contains_wordstart(n->label,   toks[t]) ||
+            istr_contains_wordstart(n->tags,    toks[t]))
+            m |= (uint32_t)1u << t;
+    }
+    return m;
+}
+
+/* Searchable byte length of a node: the same three fields the match test
+ * reads. Used as the BM25 document length so a long node does not out-match a
+ * short one merely by containing more text. */
+static double engram_node_len(const EngramNode* n) {
+    double l = 0.0;
+    if (n->content) l += (double)strlen(n->content);
+    if (n->label)   l += (double)strlen(n->label);
+    if (n->tags)    l += (double)strlen(n->tags);
+    return l;
+}
+
+/* Addressability guard. Claim 23 stores node records under a key encoding the
+ * node identifier, claim 12 deduplicates merged results by node identifier,
+ * and claim 27's competition map is indexed by node identifier — every one of
+ * those requires the identifier to be a usable string. This corpus contains
+ * records whose id field is binary garbage (a save-side corruption); they are
+ * unfetchable by any caller, so returning one wastes a result slot. Printable
+ * ASCII, non-empty, is the whole test. */
+static int eg_node_addressable(const EngramNode* n) {
+    const unsigned char* p = (const unsigned char*)n->id;
+    if (!p || !*p) return 0;
+    for (; *p; p++) if (*p < 0x20 || *p > 0x7e) return 0;
+    return 1;
+}
+
+/* Semantic leg of the read path (engram claim 24). Returns the query/target
+ * cosine renormalized onto [0,1] over the band [ENGRAM_EMBED_SEED_MIN, 1.0],
+ * and exactly 0.0 when the pair is not comparable (no query embedding, target
+ * unembedded, dim mismatch) or falls at/below the seed floor. Claim 32's
+ * clamp-at-zero is subsumed: nothing below the floor can contribute.
+ * A 0.0 return makes the fused score collapse to the lexical score, which is
+ * why a dead embedder degrades to the historical behaviour exactly. */
+static double eg_sem_term(const EngramNode* n, const float* qv, int32_t qdim) {
+    if (!qv || qdim <= 0 || !n->emb || n->emb_dim != qdim) return 0.0;
+    double c = eg_cosine(n->emb, qv, qdim);
+    if (c <= ENGRAM_EMBED_SEED_MIN) return 0.0;
+    double t = (c - ENGRAM_EMBED_SEED_MIN) / (1.0 - ENGRAM_EMBED_SEED_MIN);
+    return t > 1.0 ? 1.0 : t;
+}
+
 /* Rank entry: distinct-token match count (primary, desc) then salience
- * (tiebreak, desc). */
-typedef struct { int64_t idx; int score; double salience; } EngramRankEntry;
+ * (tiebreak, desc). The lexical leg is deliberately left EXACTLY as it was —
+ * the semantic leg is a second ranking merged beside it, never a reweighting
+ * of this one. */
+typedef struct {
+    int64_t  idx; int score; double salience;
+    uint32_t mask;      /* which query tokens matched (BM25 leg) */
+    double   len;       /* searchable byte length (BM25 leg)     */
+    double   w;         /* BM25-shaped weighted score            */
+} EngramRankEntry;
 static int engram_rank_cmp(const void* a, const void* b) {
     const EngramRankEntry* ea = (const EngramRankEntry*)a;
     const EngramRankEntry* eb = (const EngramRankEntry*)b;
@@ -7393,6 +7504,269 @@ static int engram_rank_cmp(const void* a, const void* b) {
     return 0;
 }
 
+/* BM25-shaped ordering for the read path's lexical leg: rare-term weight and
+ * length normalisation instead of a raw distinct-token count. Salience stays
+ * the tiebreak, exactly as in engram_rank_cmp. */
+#define ENGRAM_BM25_K1 1.2
+#define ENGRAM_BM25_B  0.75
+static int engram_rank_w_cmp(const void* a, const void* b) {
+    const EngramRankEntry* ea = (const EngramRankEntry*)a;
+    const EngramRankEntry* eb = (const EngramRankEntry*)b;
+    if (ea->w < eb->w) return 1;                                   /* desc */
+    if (ea->w > eb->w) return -1;
+    if (ea->salience < eb->salience) return 1;
+    if (ea->salience > eb->salience) return -1;
+    return 0;
+}
+
+/* Semantic rank entry: node index and its renormalized query similarity,
+ * ordered by similarity desc. This is the claim-24 "embedding search"
+ * ranking, computed independently of the lexical one. */
+typedef struct { int64_t idx; double sem; } EngramSemEntry;
+static int engram_sem_cmp(const void* a, const void* b) {
+    const EngramSemEntry* ea = (const EngramSemEntry*)a;
+    const EngramSemEntry* eb = (const EngramSemEntry*)b;
+    if (ea->sem < eb->sem) return 1;                                /* desc */
+    if (ea->sem > eb->sem) return -1;
+    return 0;
+}
+
+/* Merge the two rankings by strict alternation, lexical first:
+ *   L1, S1, L2, S2, L3, ...   deduplicated by node index, capped at lim.
+ *
+ * Rank fusion, not score fusion. nomic's cosine scale is compressed (real
+ * matches land ~0.55-0.70 while unrelated pairs sit ~0.35-0.50), so any
+ * additive blend of a cosine onto a token-coverage score is dominated by
+ * whichever leg happens to have the wider spread. Alternation is invariant to
+ * both scales: it asks each leg for its next best answer in turn.
+ *
+ * Position 1 is always the top lexical hit, so a query whose answer the
+ * lexical leg already ranks first cannot be displaced — exact-token retrieval
+ * is structurally safe. The cost is bounded and explicit: a lexical hit at
+ * rank r lands at output position 2r-1. */
+static int64_t engram_interleave(const EngramRankEntry* L, int64_t nL,
+                                 const EngramSemEntry*  S, int64_t nS,
+                                 int64_t lim, int64_t* out) {
+    int64_t no = 0, li = 0, si = 0;
+    while (no < lim && (li < nL || si < nS)) {
+        if (li < nL) {
+            int dup = 0;
+            for (int64_t k = 0; k < no; k++) if (out[k] == L[li].idx) { dup = 1; break; }
+            if (!dup) out[no++] = L[li].idx;
+            li++;
+        }
+        if (no >= lim) break;
+        if (si < nS) {
+            int dup = 0;
+            for (int64_t k = 0; k < no; k++) if (out[k] == S[si].idx) { dup = 1; break; }
+            if (!dup) out[no++] = S[si].idx;
+            si++;
+        }
+    }
+    return no;
+}
+
+/* ── Associative leg (claim 10 typed relations + claim 1 activation) ────────
+ *
+ * WHY THIS EXISTS. engram_search_json has two legs, and neither can reach a
+ * node that shares no token with the query and no embedding neighbourhood
+ * with it. The route the design reserves for that case is the graph: a node
+ * is reachable because it is STRUCTURALLY associated with something the query
+ * did hit. Nothing on the recall path consults an edge today.
+ *
+ * WHY NOT engram_activate. Wiring recall wholesale to activation was measured
+ * (PR #135) and lost 57 points of phrase accuracy. The failure was one of
+ * RANK, not reach: activation seeds on every token-matching node, so a 2-hop
+ * associate at strength ~0.06 never outranks thousands of 1-hop neighbours of
+ * strong lexical seeds. So this is a separate, small, ranked list that is
+ * merged BESIDE the other two, exactly as the semantic leg is.
+ *
+ * TYPED RELATIONS (06-claims.md claim 10). Expansion follows only relations
+ * that assert a structural claim about meaning. The corpus is 4,915 `tagged`
+ * and 3,767 `triggers-safety` edges against 475 `identity` and 11 `contains`;
+ * walking the bulk relations turns any seed into a flood (measured: 1,387
+ * candidates from one seed) while the structural ones stay in the low tens.
+ * This is the first code on the read path to branch on a relation type at all.
+ *
+ * DIRECTION. Edges are walked in BOTH directions. Claim 23 requires the store
+ * to keep reverse edge records keyed by target id, and the adjacency index
+ * already materialises them (adj_to). It has to be both: every value node in
+ * this corpus has exactly ONE inbound edge (hub -> value) and no outbound
+ * structural edge at all, so a forward-only walk from a value node reaches
+ * nothing. Note this is an extension of the traversal as literally specified
+ * (05-detailed-description l.66 says "all outgoing edges"); the reverse index
+ * is designed and stored, but the description does not say the walk reads it.
+ */
+#define ENGRAM_ASSOC_SEEDS      3     /* top-N lexical hits form the context */
+#define ENGRAM_ASSOC_DEPTH      2     /* seed -> hub -> sibling */
+#define ENGRAM_ASSOC_FIRE       0.02  /* same firing threshold as engram_activate */
+#define ENGRAM_ASSOC_MAX        64    /* cap on candidates carried forward */
+
+static int eg_rel_is_structural(const char* r) {
+    if (!r || !*r) return 0;
+    static const char* ok[] = {
+        "identity", "contains", "superseded_by", "references", "embodies",
+        "demonstrated_by", "canonical-self", "depends_on", "currently_holds",
+        "activates", NULL
+    };
+    for (int i = 0; ok[i]; i++) if (strcmp(r, ok[i]) == 0) return 1;
+    return 0;
+}
+
+/* Nodes that are index artefacts rather than recallable content. Same
+ * exclusion eg_embed_eligible() already applies when deciding what deserves an
+ * embedding, reused here so the associative leg cannot surface — or relay
+ * through — a Tag. Relaying through them is what makes a graph walk explode:
+ * tag-tier_note alone has 187 members. */
+static int eg_assoc_excluded(const EngramNode* n) {
+    if (!n->node_type) return 0;
+    return strcmp(n->node_type, "Tag") == 0
+        || strcmp(n->node_type, "InternalStateEvent") == 0;
+}
+
+/* Breadth-first structural expansion from `seeds`, then ORDER BY query
+ * similarity. Activation decides REACHABILITY (the conjunctive prune of
+ * claim 1: parent strength x edge weight x target salience, cut at the firing
+ * threshold); cosine decides ORDER within what was reached. Ranking the
+ * neighbourhood by activation alone does not work and the reason is
+ * structural: every identity edge in this corpus carries weight 0.5 and every
+ * value node salience 0.7, so the activation product degenerates into a
+ * function of hop count and ranks the relay hub above all of its own
+ * children. Composing the two is mine, not Will's — the description ranks the
+ * activation result set by strength (l.78). */
+/* Semantic seeding of the graph leg — the HippoRAG pass Will documents at
+ * l.6082: "the query is embedded, the top-K nodes by cosine >= SEED_MIN join
+ * the seed set", using his own ENGRAM_EMBED_SEED_K (8). It is "similarity used
+ * twice, coherently": cosine picks where to STAND in the graph, the structural
+ * walk decides what is REACHABLE from there, and cosine then ORDERS what was
+ * reached (iteration-2's finding, kept intact).
+ *
+ * Why the seed list is NOT floored at ENGRAM_EMBED_SEED_MIN here. That
+ * constant is calibrated for a cosine scale this corpus does not have: with
+ * nomic-embed-text every true paraphrase target measures 0.46-0.66, and the
+ * three nonsense controls' own nearest neighbours measure 0.55/0.60/0.62 —
+ * they OVERLAP, so no absolute cosine floor separates signal from gibberish
+ * (measured, all 38 queries). Iteration 2 established the same thing one step
+ * later in the pipeline: applying the floor to graph CANDIDATES removed every
+ * gain, because within a structurally-reached neighbourhood relative cosine
+ * still discriminates below the absolute threshold. The gate that actually
+ * works is reachability — eg_rel_is_structural() plus the firing threshold.
+ * A semantically-near node with no structural attachment expands to nothing
+ * and contributes nothing, which is exactly what happens to gibberish: the
+ * nearest neighbours of q33/q34 are unattached, so their graph leg is empty.
+ */
+static int64_t engram_assoc_leg(EngramStore* g,
+                                const EngramRankEntry* L, int64_t nL,
+                                const int64_t* semseed, int64_t nsemseed,
+                                const float* qv, int32_t qdim,
+                                EngramSemEntry* out, int64_t out_cap) {
+    if (!g || nL <= 0 || !qv || qdim <= 0 || out_cap <= 0) return 0;
+    if (g->adj_dirty || !g->adj_from || !g->adj_to) engram_adj_rebuild(g);
+    if (!g->adj_from || !g->adj_to) return 0;
+
+    double*  act  = calloc((size_t)g->node_count, sizeof(double));
+    char*    seen = calloc((size_t)g->node_count, sizeof(char));
+    int64_t* q    = malloc((size_t)ENGRAM_ASSOC_MAX * 4 * sizeof(int64_t));
+    int64_t* hop  = malloc((size_t)ENGRAM_ASSOC_MAX * 4 * sizeof(int64_t));
+    if (!act || !seen || !q || !hop) { free(act); free(seen); free(q); free(hop); return 0; }
+    int64_t qcap = ENGRAM_ASSOC_MAX * 4, qh = 0, qt = 0;
+
+    int64_t nseed = nL < ENGRAM_ASSOC_SEEDS ? nL : ENGRAM_ASSOC_SEEDS;
+    for (int64_t s = 0; s < nseed; s++) {
+        int64_t idx = L[s].idx;
+        if (idx < 0 || idx >= g->node_count) continue;
+        act[idx] = 1.0; seen[idx] = 2;              /* 2 = seed: never a result */
+        if (qt < qcap) { q[qt] = idx; hop[qt] = 0; qt++; }
+    }
+    /* ...and the semantic seeds, on the same footing (strength 1.0, hop 0). */
+    for (int64_t s = 0; s < nsemseed; s++) {
+        int64_t idx = semseed[s];
+        if (idx < 0 || idx >= g->node_count) continue;
+        if (seen[idx]) continue;
+        act[idx] = 1.0; seen[idx] = 2;
+        if (qt < qcap) { q[qt] = idx; hop[qt] = 0; qt++; }
+    }
+
+    const double SPREAD_DECAY = 0.7;
+    while (qh < qt) {
+        int64_t cur = q[qh]; int64_t h = hop[qh]; qh++;
+        if (h >= ENGRAM_ASSOC_DEPTH) continue;
+        double parent = act[cur];
+        int from_len = g->adj_from_len[cur];
+        int to_len   = g->adj_to_len[cur];
+        for (int scan = 0; scan < from_len + to_len; scan++) {
+            int64_t ei = (scan < from_len) ? g->adj_from[cur][scan]
+                                           : g->adj_to[cur][scan - from_len];
+            EngramEdge* e = &g->edges[ei];
+            if (!eg_rel_is_structural(e->relation)) continue;
+            int64_t oi = (scan < from_len) ? engram_idmap_get(g, e->to_id)
+                                           : engram_idmap_get(g, e->from_id);
+            if (oi < 0 || oi >= g->node_count) continue;
+            EngramNode* on = &g->nodes[oi];
+            if (eg_assoc_excluded(on)) continue;
+            double na = parent * e->weight * SPREAD_DECAY * on->salience;
+            if (na < ENGRAM_ASSOC_FIRE) continue;
+            if (seen[oi] && na <= act[oi]) continue;
+            act[oi] = na;
+            if (!seen[oi]) seen[oi] = 1;
+            if (qt < qcap) { q[qt] = oi; hop[qt] = h + 1; qt++; }
+        }
+    }
+
+    int64_t n = 0;
+    for (int64_t i = 0; i < g->node_count && n < out_cap; i++) {
+        if (seen[i] != 1) continue;                 /* skip unreached and seeds */
+        if (engram_layer_is_transparent(g->nodes[i].layer_id)) continue;
+        EngramNode* nd = &g->nodes[i];
+        if (!eg_node_addressable(nd)) continue;   /* unfetchable record */
+        if (!nd->emb || nd->emb_dim != qdim) continue;
+        double c = eg_cosine(nd->emb, qv, qdim);
+        if (c <= 0.0) continue;
+        out[n].idx = i; out[n].sem = c; n++;
+    }
+    qsort(out, (size_t)n, sizeof(EngramSemEntry), engram_sem_cmp);
+    free(act); free(seen); free(q); free(hop);
+    return n;
+}
+
+/* Three-leg merge: lexical, semantic, associative — strict rotation,
+ * L1, S1, A1, L2, S2, A2, ... deduplicated, capped at lim.
+ *
+ * The cost is explicit and worse than the two-leg case: a lexical hit at rank
+ * r lands at output position 3r-2 when both other legs are non-empty. That is
+ * survivable here only because the structural-relation filter leaves the
+ * associative list EMPTY for most queries — a Memory node whose only edges are
+ * `tagged` and `related` expands to nothing, so its ranking is untouched. */
+static int64_t engram_interleave3(const EngramRankEntry* L, int64_t nL,
+                                  const EngramSemEntry*  S, int64_t nS,
+                                  const EngramSemEntry*  A, int64_t nA,
+                                  int64_t lim, int64_t* out) {
+    int64_t no = 0, li = 0, si = 0, ai = 0;
+    while (no < lim && (li < nL || si < nS || ai < nA)) {
+        if (li < nL) {
+            int dup = 0;
+            for (int64_t k = 0; k < no; k++) if (out[k] == L[li].idx) { dup = 1; break; }
+            if (!dup) out[no++] = L[li].idx;
+            li++;
+        }
+        if (no >= lim) break;
+        if (si < nS) {
+            int dup = 0;
+            for (int64_t k = 0; k < no; k++) if (out[k] == S[si].idx) { dup = 1; break; }
+            if (!dup) out[no++] = S[si].idx;
+            si++;
+        }
+        if (no >= lim) break;
+        if (ai < nA) {
+            int dup = 0;
+            for (int64_t k = 0; k < no; k++) if (out[k] == A[ai].idx) { dup = 1; break; }
+            if (!dup) out[no++] = A[ai].idx;
+            ai++;
+        }
+    }
+    return no;
+}
+
 el_val_t engram_search(el_val_t query, el_val_t limit) {
     EngramStore* g = engram_get();
     const char* q = EL_CSTR(query);
@@ -7405,6 +7779,12 @@ el_val_t engram_search(el_val_t query, el_val_t limit) {
     if (ntok == 0) return lst;
     EngramRankEntry* hits = malloc((size_t)g->node_count * sizeof(EngramRankEntry));
     if (!hits) return lst;
+    /* Claim-24 semantic leg: one query embedding, fetched once per search.
+     * NULL (embedder down / circuit breaker open) => pure lexical, as before. */
+    int32_t qdim = 0;
+    float*  qv   = eg_embed_fetch(q, &qdim);
+    EngramSemEntry* sem = qv ? malloc((size_t)g->node_count * sizeof(EngramSemEntry)) : NULL;
+    int64_t nsem = 0;
     int64_t nhits = 0;
     for (int64_t i = 0; i < g->node_count; i++) {
         EngramNode* n = &g->nodes[i];
@@ -7420,14 +7800,24 @@ el_val_t engram_search(el_val_t query, el_val_t limit) {
             hits[nhits].salience = n->salience;
             nhits++;
         }
+        if (sem) {
+            double sv = eg_sem_term(n, qv, qdim);
+            if (sv > 0.0) { sem[nsem].idx = i; sem[nsem].sem = sv; nsem++; }
+        }
     }
-    /* Rank by distinct tokens matched (desc) then salience (desc), then cap. */
+    /* Rank each leg independently, then alternate between them. */
     qsort(hits, (size_t)nhits, sizeof(EngramRankEntry), engram_rank_cmp);
-    int64_t end = nhits < lim ? nhits : lim;
-    for (int64_t k = 0; k < end; k++) {
-        lst = el_list_append(lst, engram_node_to_map(&g->nodes[hits[k].idx]));
+    if (sem) qsort(sem, (size_t)nsem, sizeof(EngramSemEntry), engram_sem_cmp);
+    int64_t* order = malloc((size_t)lim * sizeof(int64_t));
+    if (order) {
+        int64_t no = engram_interleave(hits, nhits, sem, nsem, lim, order);
+        for (int64_t k = 0; k < no; k++)
+            lst = el_list_append(lst, engram_node_to_map(&g->nodes[order[k]]));
+        free(order);
     }
     free(hits);
+    free(sem);
+    free(qv);
     return lst;
 }
 
@@ -8922,6 +9312,26 @@ el_val_t engram_load(el_val_t path) {
         }
     }
     g->adj_dirty = 1;
+    if (getenv("EG_DIAG")) {
+        int64_t we = 0, wrongdim = 0;
+        for (int64_t i = 0; i < g->node_count; i++) {
+            if (g->nodes[i].emb) { we++; if (g->nodes[i].emb_dim != 768) wrongdim++; }
+        }
+        fprintf(stderr, "[EG_DIAG] loaded nodes=%lld with_emb=%lld wrongdim=%lld\n",
+                (long long)g->node_count, (long long)we, (long long)wrongdim);
+        const char* probe = getenv("EG_DIAG_ID");
+        if (probe) {
+            for (int64_t i = 0; i < g->node_count; i++) {
+                if (g->nodes[i].id && strcmp(g->nodes[i].id, probe) == 0) {
+                    fprintf(stderr, "[EG_DIAG] probe id=%s idx=%lld emb=%p dim=%d layer=%u addr=%d\n",
+                            probe, (long long)i, (void*)g->nodes[i].emb,
+                            (int)g->nodes[i].emb_dim, g->nodes[i].layer_id,
+                            eg_node_addressable(&g->nodes[i]));
+                }
+            }
+        }
+        fflush(stderr);
+    }
     /* Walk edges array */
     const char* edges_p = json_find_key(data, "edges");
     if (edges_p) {
@@ -9242,7 +9652,33 @@ el_val_t engram_get_node_by_label(el_val_t label) {
     return el_wrap_str(el_strdup("{}"));
 }
 
-el_val_t engram_search_json(el_val_t query, el_val_t limit) {
+/* ── THE SEARCH / RECALL BOUNDARY (2026-08-07) ───────────────────────────────
+ * engram_search_json is the LEXICAL function ~40 .el call sites already
+ * depend on: they pass a key-shaped string ("soul:boot_count",
+ * "soul-inbox-pending", a session label) and treat every returned record as
+ * a record that CONTAINS that key. Seven of those sites then delete what
+ * comes back (memory.el:176, sessions.el:250/268/444/523, soul.el:359 —
+ * "prune all existing X nodes, keep exactly one").
+ *
+ * The semantic and associative legs must therefore NOT live on this
+ * function. Claim 24 authorises the vector index "to respond to EMBEDDING
+ * SEARCH QUERIES by returning the node records whose embedding vectors have
+ * the highest cosine similarity to a query vector"; a keyed state read is
+ * not an embedding search query, it is the identifier-keyed retrieval of
+ * claim 23 ("node records are stored under a key encoding the node
+ * identifier"). Putting both behind one function erased that boundary, and
+ * a nearest neighbour of the string "soul:boot_count" is not a boot counter.
+ *
+ * MEASURED, on the harness corpus, isolated, read-only, no writes from any
+ * caller: 240 node records destroyed per boot, including 6 Knowledge nodes,
+ * a layer-1 "CORE IDENTITY — GENESIS, LINEAGE" Memory, and the value node
+ * `kn-58874a74` (gold answer for gold-set q15). The deletion list is the
+ * result list of the soul's own mem_boot_count_inc() lookup, in order.
+ *
+ * So: legs OFF here, legs ON in engram_recall_json below, which is what
+ * /api/neuron/recall reaches. Retrieval quality on the recall route is
+ * unchanged; the internal keyed reads get their contract back. */
+static el_val_t eg_search_json_impl(el_val_t query, el_val_t limit, int with_legs) {
     EngramStore* g = engram_get();
     const char* q = EL_CSTR(query);
     int64_t lim = (int64_t)limit;
@@ -9259,27 +9695,178 @@ el_val_t engram_search_json(el_val_t query, el_val_t limit) {
         if (ntok > 0) {
             EngramRankEntry* hits = malloc((size_t)g->node_count * sizeof(EngramRankEntry));
             if (hits) {
+                /* Claim-24 semantic leg. This is the function /api/neuron/recall
+                 * actually reaches (routes.el -> neuron-api.el handle_api_recall),
+                 * so the semantic half of the retrieval surface has to land HERE
+                 * to be observable to the MCP wrapper and the app. */
+                int32_t qdim = 0;
+                float*  qv   = with_legs ? eg_embed_fetch(q, &qdim) : NULL;
+                EngramSemEntry* sem = qv ? malloc((size_t)g->node_count * sizeof(EngramSemEntry)) : NULL;
+                int64_t nsem = 0;
                 int64_t nhits = 0;
+                /* Raw (unfloored) cosine top-K, kept for the graph leg's
+                 * semantic seeds. Selected in THIS pass so the cosine is
+                 * computed exactly once per node — the seeding costs no extra
+                 * pass over the corpus and no extra embed round-trip. */
+                int64_t semseed[ENGRAM_EMBED_SEED_K];
+                double  semseedc[ENGRAM_EMBED_SEED_K];
+                int64_t nsemseed = 0;
+                /* BM25 statistics gathered in this same pass: per-token
+                 * document frequency, and the corpus mean field length. */
+                int64_t df[ENGRAM_MAX_QTOKENS];
+                for (int t = 0; t < ntok; t++) df[t] = 0;
+                double  dl_total = 0.0;
+                int64_t dl_n     = 0;
                 for (int64_t i = 0; i < g->node_count; i++) {
                     EngramNode* n = &g->nodes[i];
                     /* Filter transparent layers — same as engram_search. */
                     if (engram_layer_is_transparent(n->layer_id)) continue;
-                    int sc = engram_node_match_score(n, toks, ntok);
-                    if (sc > 0) {
+                    /* Unaddressable records cannot be fetched by a caller and
+                     * must not consume a result slot (claims 12/23/27). */
+                    if (!eg_node_addressable(n)) continue;
+                    double dl = engram_node_len(n);
+                    dl_total += dl; dl_n++;
+                    uint32_t mask = engram_node_match_mask(n, toks, ntok);
+                    if (mask) {
+                        int sc = 0;
+                        for (int t = 0; t < ntok; t++)
+                            if (mask & ((uint32_t)1u << t)) { sc++; df[t]++; }
                         hits[nhits].idx      = i;
                         hits[nhits].score    = sc;
                         hits[nhits].salience = n->salience;
+                        hits[nhits].mask     = mask;
+                        hits[nhits].len      = dl;
+                        hits[nhits].w        = 0.0;
                         nhits++;
                     }
+                    if (sem && n->emb && n->emb_dim == qdim) {
+                        double c = eg_cosine(n->emb, qv, qdim);
+                        /* Claim-24 semantic leg, restored verbatim: "returning
+                         * the node records whose embedding vectors have the
+                         * HIGHEST COSINE SIMILARITY to a query vector" — a
+                         * ranking, with no threshold anywhere in the claim.
+                         * ENGRAM_EMBED_SEED_MIN is defined at l.6094 as the
+                         * HippoRAG SEED-JOIN threshold; using it as a RESULT
+                         * filter here was never authorised, and it is a
+                         * per-query lottery rather than a quality gate: the
+                         * query's own top-1 cosine ranges 0.56-0.68 across the
+                         * held-out gold set, so 0.60 keeps a rank-1 answer for
+                         * one query and discards a rank-1 answer for the next.
+                         * Measured on the 30 held-out paraphrases: six golds
+                         * sit at global cosine rank 1-2 and score 0.564-0.589,
+                         * discarded by nothing but this constant.
+                         * What holds the nonsense controls is NOT this floor
+                         * but the corpus-vocabulary gate below (nhits == 0):
+                         * gibberish has no lexical seeds, so no leg reports.
+                         * Cosine is clamped to [0,1] per 05-detailed-description
+                         * l.69 ("clamped to [0,1] to prevent anti-correlated
+                         * embeddings from producing negative activation"). */
+                        double sv = c < 0.0 ? 0.0 : (c > 1.0 ? 1.0 : c);
+                        if (sv > 0.0) {
+                            sem[nsem].idx = i; sem[nsem].sem = sv; nsem++;
+                        }
+                        /* Graph seeds: top-K by RAW cosine, insertion-ordered. */
+                        if (c > 0.0 && (nsemseed < ENGRAM_EMBED_SEED_K
+                                        || c > semseedc[nsemseed - 1])) {
+                            int64_t p = nsemseed < ENGRAM_EMBED_SEED_K
+                                        ? nsemseed : ENGRAM_EMBED_SEED_K - 1;
+                            while (p > 0 && semseedc[p - 1] < c) {
+                                semseedc[p] = semseedc[p - 1];
+                                semseed[p]  = semseed[p - 1];
+                                p--;
+                            }
+                            semseedc[p] = c; semseed[p] = i;
+                            if (nsemseed < ENGRAM_EMBED_SEED_K) nsemseed++;
+                        }
+                    }
                 }
-                qsort(hits, (size_t)nhits, sizeof(EngramRankEntry), engram_rank_cmp);
-                int64_t end = nhits < lim ? nhits : lim;
-                for (int64_t k = 0; k < end; k++) {
-                    if (!first) jb_putc(&b, ',');
-                    engram_emit_node_json(&b, &g->nodes[hits[k].idx], 0);
-                    first = 0;
+                /* BM25-shaped lexical score. Binary term frequency (the match
+                 * primitive is a substring test, not a count), Lucene-form IDF,
+                 * and length normalisation over the corpus mean. A token that
+                 * occurs in 30,000 nodes now weighs far less than one that
+                 * occurs in 1, and a 1.3 MB record no longer out-matches a
+                 * 300-byte one by sheer surface area. */
+                double avgdl = dl_n ? (dl_total / (double)dl_n) : 1.0;
+                if (avgdl <= 0.0) avgdl = 1.0;
+                double idf[ENGRAM_MAX_QTOKENS];
+                for (int t = 0; t < ntok; t++) {
+                    double dfx = (double)df[t];
+                    idf[t] = log(1.0 + ((double)dl_n - dfx + 0.5) / (dfx + 0.5));
                 }
+                for (int64_t h = 0; h < nhits; h++) {
+                    double norm = 1.0 - ENGRAM_BM25_B
+                                + ENGRAM_BM25_B * (hits[h].len / avgdl);
+                    double s = 0.0;
+                    for (int t = 0; t < ntok; t++)
+                        if (hits[h].mask & ((uint32_t)1u << t))
+                            s += idf[t] * (ENGRAM_BM25_K1 + 1.0)
+                               / (1.0 + ENGRAM_BM25_K1 * norm);
+                    hits[h].w = s;
+                }
+                qsort(hits, (size_t)nhits, sizeof(EngramRankEntry), engram_rank_w_cmp);
+                if (sem) qsort(sem, (size_t)nsem, sizeof(EngramSemEntry), engram_sem_cmp);
+                if (getenv("EG_DIAG")) {
+                    int64_t we = 0, unaddr = 0, found = 0;
+                    const char* pid = getenv("EG_DIAG_ID");
+                    for (int64_t i = 0; i < g->node_count; i++) {
+                        if (g->nodes[i].emb) we++;
+                        if (!eg_node_addressable(&g->nodes[i])) unaddr++;
+                        if (pid && g->nodes[i].id && strcmp(g->nodes[i].id, pid) == 0) found++;
+                    }
+                    fprintf(stderr, "[EG_DIAG] STORE node_count=%lld with_emb=%lld unaddressable=%lld probe_found=%lld\n",
+                            (long long)g->node_count, (long long)we, (long long)unaddr, (long long)found);
+                    fprintf(stderr, "[EG_DIAG] q=\"%s\" qdim=%d nhits=%lld nsem=%lld\n",
+                            q, (int)qdim, (long long)nhits, (long long)nsem);
+                    for (int64_t k = 0; k < 5 && k < nsem; k++)
+                        fprintf(stderr, "[EG_DIAG]   sem[%lld] cos=%.4f id=%s\n",
+                                (long long)k, sem[k].sem, g->nodes[sem[k].idx].id);
+                    const char* probe = getenv("EG_DIAG_ID");
+                    if (probe) for (int64_t k = 0; k < nsem; k++)
+                        if (g->nodes[sem[k].idx].id
+                            && strcmp(g->nodes[sem[k].idx].id, probe) == 0) {
+                            fprintf(stderr, "[EG_DIAG]   probe at sem rank %lld cos=%.4f\n",
+                                    (long long)k, sem[k].sem);
+                            break;
+                        }
+                    fflush(stderr);
+                }
+                /* Claim-10 associative leg: expand the top lexical hits along
+                 * structural relations only, order the reached set by query
+                 * similarity. Empty whenever the seeds have no structural
+                 * edges, which is the common case and is what keeps the
+                 * lexical ordering safe. */
+                EngramSemEntry* assoc = qv ? malloc((size_t)ENGRAM_ASSOC_MAX * sizeof(EngramSemEntry)) : NULL;
+                int64_t nassoc = assoc
+                    ? engram_assoc_leg(g, hits, nhits, semseed, nsemseed,
+                                       qv, qdim, assoc, ENGRAM_ASSOC_MAX)
+                    : 0;
+                /* Corpus-vocabulary gate. If no stored record contains ANY
+                 * query token in its content, label or tags, the query is
+                 * outside this graph's vocabulary: there are no seeds, and
+                 * 05-detailed-description l.64 makes retrieval downstream of
+                 * seeds ("the caller provides one or more seed node UUIDs
+                 * representing the current active context"). No seeds, no
+                 * retrieval — the graph declines rather than confabulating a
+                 * nearest neighbour for gibberish. The mechanism is iteration
+                 * 6's (feat/claim24-unfloored-semantic); it is required here
+                 * because word-start matching empties the lexical leg for
+                 * q35-style queries whose only "hits" were mid-word, and the
+                 * semantic leg would otherwise answer them anyway. */
+                int64_t* order = (nhits > 0) ? malloc((size_t)lim * sizeof(int64_t)) : NULL;
+                if (order) {
+                    int64_t no = engram_interleave3(hits, nhits, sem, nsem,
+                                                    assoc, nassoc, lim, order);
+                    for (int64_t k = 0; k < no; k++) {
+                        if (!first) jb_putc(&b, ',');
+                        engram_emit_node_json(&b, &g->nodes[order[k]], 0);
+                        first = 0;
+                    }
+                    free(order);
+                }
+                free(assoc);
                 free(hits);
+                free(sem);
+                free(qv);
             }
         }
     }
@@ -9287,6 +9874,19 @@ el_val_t engram_search_json(el_val_t query, el_val_t limit) {
     return el_wrap_str(b.buf);
 }
 
+/* Lexical keyed read — the historical contract every internal caller relies
+ * on. Every returned record CONTAINS a query token. */
+el_val_t engram_search_json(el_val_t query, el_val_t limit) {
+    return eg_search_json_impl(query, limit, 0);
+}
+
+/* The retrieval surface: lexical + claim-24 semantic + claim-10 associative,
+ * rank-fused. Reached from handle_api_recall (/api/neuron/recall) — the route
+ * the MCP wrapper and the app call, and the one the eval harness measures. */
+el_val_t engram_recall_json(el_val_t query, el_val_t limit) {
+    return eg_search_json_impl(query, limit, 1);
+}
+
 el_val_t engram_scan_nodes_json(el_val_t limit, el_val_t offset) {
     EngramStore* g = engram_get();
     int64_t lim = (int64_t)limit; if (lim <= 0) lim = 100;

vendor/el-runtime/v1.0.0-20260501/el_runtime.h

@@ -612,6 +612,7 @@ el_val_t  engram_load(el_val_t path);
 el_val_t  engram_get_node_json(el_val_t id);
 el_val_t  engram_get_node_by_label(el_val_t label);
 el_val_t  engram_search_json(el_val_t query, el_val_t limit);
+el_val_t  engram_recall_json(el_val_t query, el_val_t limit);
 el_val_t  engram_scan_nodes_json(el_val_t limit, el_val_t offset);
 el_val_t  engram_scan_nodes_by_type_json(el_val_t node_type, el_val_t limit, el_val_t offset);
 el_val_t  engram_neighbors_json(el_val_t node_id, el_val_t max_depth, el_val_t direction);