feat(engram): Will's Layer-2 executive filter (claims 44/45) on the recall read path

Claim 44 requires a second pass that computes a working memory weight
(background activation x goal-state attentional bias x confidence) and
promotes only what clears a per-type threshold; claim 45 keeps the
un-promoted field retained rather than discarded. That pass exists in
engram_activate and nowhere on the route /api/neuron/recall reaches.

engram_search_json now splits each of its three legs into promoted and
suppressed sublists and rotates the promoted material into the head of
the result, background-only behind it (05-detailed-description l.221:
'promoted nodes first ... followed by background-only nodes').

MEASURED: net +0 queries vs its parent feat/bm25-lexical-leg on the
38-query gold set. NOT-SHOWN. hit@5 74.3% both sides; recall@10
61.8 -> 63.2%, MRR@10 0.502 -> 0.524, latency p50 1184 -> 1198ms.

The first cut (results-execfilter.json, kept as evidence) fed pass 2 the
semantic leg's shift-and-floor value instead of raw cosine and lost 6
queries (paraphrase 61.5 -> 23.1%, p=0.0312).

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>

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/cmp-bm25-vs-execfilter.json

@@ -0,0 +1,138 @@
+{
+ "baseline": "bm25lex",
+ "candidate": "execfilter",
+ "n_shared_queries": 38,
+ "fixed_by_candidate": [],
+ "broken_by_candidate": [
+  "q15",
+  "q16",
+  "q20",
+  "q21",
+  "q26",
+  "q37"
+ ],
+ "discordant": 6,
+ "net_queries": -6,
+ "mcnemar_exact_p": 0.03125,
+ "min_detectable_swing_queries": 6,
+ "observed_run_to_run_drift_queries": 0,
+ "noise_floor_queries": 6,
+ "verdict": "candidate worse",
+ "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": 0.6,
+  "recall@5": 0.41518699554413835,
+  "recall@10": 0.4869109065537637,
+  "precision@5": 0.18285714285714288,
+  "mrr@10": 0.4493197278911565,
+  "nonsense_clean": "2/3",
+  "superseded_outranks": "1/3",
+  "latency_ms_p50": 1183.3,
+  "latency_ms_p95": 1637.5,
+  "latency_ms_max": 1672.5,
+  "errors": 0,
+  "by_category": {
+   "associative": {
+    "n": 6,
+    "hit@5": 0.6666666666666666,
+    "recall@5": 0.11421911421911422,
+    "recall@10": 0.3146853146853147,
+    "mrr@10": 0.2916666666666667
+   },
+   "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": 0.23076923076923078,
+    "recall@5": 0.23076923076923078,
+    "recall@10": 0.3076923076923077,
+    "mrr@10": 0.12637362637362637
+   },
+   "phrase": {
+    "n": 7,
+    "hit@5": 1.0,
+    "recall@5": 0.5494614512471656,
+    "recall@10": 0.5933956916099773,
+    "mrr@10": 0.8333333333333334
+   },
+   "superseded": {
+    "n": 3,
+    "hit@5": 0.3333333333333333,
+    "recall@5": 0.3333333333333333,
+    "recall@10": 0.3333333333333333,
+    "mrr@10": 0.16666666666666666,
+    "outranks": 1
+   }
+  }
+ },
+ "repeat_variance": {}
+}

tools/retrieval-eval/cmp-bm25-vs-execfilter2.json

@@ -0,0 +1,131 @@
+{
+ "baseline": "bm25lex",
+ "candidate": "execfilter2",
+ "n_shared_queries": 38,
+ "fixed_by_candidate": [],
+ "broken_by_candidate": [],
+ "discordant": 0,
+ "net_queries": 0,
+ "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,
+    "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": {
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+    "hit@5": 1.0,
+    "recall@5": 0.5494614512471656,
+    "recall@10": 0.6023242630385487,
+    "mrr@10": 0.8214285714285714
+   },
+   "superseded": {
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+    "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": 0.5580441384012813,
+  "recall@10": 0.631553763696621,
+  "precision@5": 0.2114285714285715,
+  "mrr@10": 0.5235714285714286,
+  "nonsense_clean": "2/3",
+  "superseded_outranks": "2/3",
+  "latency_ms_p50": 1198.3,
+  "latency_ms_p95": 1632.6,
+  "latency_ms_max": 1664.0,
+  "errors": 0,
+  "by_category": {
+   "associative": {
+    "n": 6,
+    "hit@5": 0.6666666666666666,
+    "recall@5": 0.11421911421911422,
+    "recall@10": 0.3146853146853147,
+    "mrr@10": 0.2916666666666667
+   },
+   "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": 0.3230769230769231
+   },
+   "phrase": {
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+    "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
+   }
+  }
+ },
+ "repeat_variance": {}
+}

tools/retrieval-eval/cmp-semseed-vs-execfilter2.json

@@ -0,0 +1,134 @@
+{
+ "baseline": "semseed",
+ "candidate": "execfilter2",
+ "n_shared_queries": 38,
+ "fixed_by_candidate": [
+  "q10",
+  "q11"
+ ],
+ "broken_by_candidate": [],
+ "discordant": 2,
+ "net_queries": 2,
+ "mcnemar_exact_p": 0.5,
+ "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": 0.6857142857142857,
+  "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": {
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+    "hit@5": 0.7142857142857143,
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+    "recall@10": 0.5150226757369615,
+    "mrr@10": 0.6507936507936508
+   },
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+    "mrr@10": 0.20833333333333334,
+    "outranks": 2
+   }
+  }
+ },
+ "candidate_aggregate": {
+  "n_queries": 38,
+  "n_scored": 35,
+  "hit@5": 0.7428571428571429,
+  "recall@5": 0.5580441384012813,
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+  "mrr@10": 0.5235714285714286,
+  "nonsense_clean": "2/3",
+  "superseded_outranks": "2/3",
+  "latency_ms_p50": 1198.3,
+  "latency_ms_p95": 1632.6,
+  "latency_ms_max": 1664.0,
+  "errors": 0,
+  "by_category": {
+   "associative": {
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+    "mrr@10": 0.2916666666666667
+   },
+   "exact_rare": {
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+    "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": 0.3230769230769231
+   },
+   "phrase": {
+    "n": 7,
+    "hit@5": 1.0,
+    "recall@5": 0.5494614512471656,
+    "recall@10": 0.6023242630385487,
+    "mrr@10": 0.8214285714285714
+   },
+   "superseded": {
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+    "hit@5": 0.3333333333333333,
+    "recall@5": 0.3333333333333333,
+    "recall@10": 0.6666666666666666,
+    "mrr@10": 0.20833333333333334,
+    "outranks": 2
+   }
+  }
+ },
+ "repeat_variance": {}
+}

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,
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+    "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,
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+    "recall@10": 0.6153846153846154,
+    "mrr@10": 0.2846153846153846
+   },
+   "phrase": {
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+   },
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+    "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-hybrid-vs-semseed.json

@@ -0,0 +1,154 @@
+{
+ "baseline": "hybrid-semantic",
+ "candidate": "semseed",
+ "n_shared_queries": 38,
+ "fixed_by_candidate": [
+  "q18",
+  "q19",
+  "q22",
+  "q27",
+  "q28",
+  "q29",
+  "q31"
+ ],
+ "broken_by_candidate": [
+  "q11"
+ ],
+ "discordant": 8,
+ "net_queries": 6,
+ "mcnemar_exact_p": 0.0703125,
+ "min_detectable_swing_queries": 6,
+ "observed_run_to_run_drift_queries": 0,
+ "noise_floor_queries": 6,
+ "verdict": "candidate better",
+ "baseline_aggregate": {
+  "n_queries": 38,
+  "n_scored": 35,
+  "hit@5": 0.5142857142857142,
+  "recall@5": 0.4409013605442177,
+  "recall@10": 0.5047619047619047,
+  "precision@5": 0.15428571428571433,
+  "mrr@10": 0.38746031746031745,
+  "nonsense_clean": "2/3",
+  "superseded_outranks": "2/3",
+  "latency_ms_p50": 1219.7,
+  "latency_ms_p95": 1667.1,
+  "latency_ms_max": 1720.2,
+  "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": 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": 0.4902210884353741,
+    "recall@10": 0.6666666666666666,
+    "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": 0.5142857142857142,
+   "hit@5_max": 0.5142857142857142,
+   "spread_queries": 0
+  },
+  "candidate": {
+   "runs": 2,
+   "hit@5_min": 0.6857142857142857,
+   "hit@5_max": 0.6857142857142857,
+   "spread_queries": 0
+  }
+ }
+}

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

@@ -0,0 +1,147 @@
+{
+ "baseline": "semseed",
+ "candidate": "bm25lex",
+ "n_shared_queries": 38,
+ "fixed_by_candidate": [
+  "q10",
+  "q11"
+ ],
+ "broken_by_candidate": [],
+ "discordant": 2,
+ "net_queries": 2,
+ "mcnemar_exact_p": 0.5,
+ "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": 0.6857142857142857,
+  "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
+   }
+  }
+ },
+ "candidate_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
+   }
+  }
+ },
+ "repeat_variance": {
+  "baseline": {
+   "runs": 2,
+   "hit@5_min": 0.6857142857142857,
+   "hit@5_max": 0.6857142857142857,
+   "spread_queries": 0
+  },
+  "candidate": {
+   "runs": 2,
+   "hit@5_min": 0.7428571428571429,
+   "hit@5_max": 0.7428571428571429,
+   "spread_queries": 0
+  }
+ }
+}

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/results-bm25lex-r2.json

@@ -0,0 +1,959 @@
+{
+ "label": "bm25lex-r2",
+ "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": 7894,
+ "wall_clock_s": 50.1,
+ "child_pid": 90371,
+ "child_confirmed_dead": true,
+ "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": 1183.8,
+  "latency_ms_p95": 1611.3,
+  "latency_ms_max": 1654.7,
+  "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
+   }
+  }
+ },
+ "rows": [
+  {
+   "id": "q01",
+   "category": "exact_rare",
+   "query": "unjailbreakable",
+   "returned": [
+    "mem-7f61beb4-271c-4feb-9f6e-1c9c837a6226"
+   ],
+   "n_returned": 1,
+   "latency_ms": 282.6,
+   "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",
+    "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",
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+  },
+  {
+   "id": "q03",
+   "category": "exact_rare",
+   "query": "cartabandonedevent",
+   "returned": [
+    "mem-1ba7c67d-85b9-4c2e-9fe2-39f8b0477091"
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+   "mrr@10": 1.0
+  },
+  {
+   "id": "q04",
+   "category": "exact_rare",
+   "query": "pre-apprenticeship",
+   "returned": [
+    "mem-89c02aae-d3ca-43f9-9e5d-eb369896276c"
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+   "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_"
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+  {
+   "id": "q06",
+   "category": "exact_rare",
+   "query": "clear-eyed",
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+   "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_",
+    "bl-79028eed-c330-4724-9402-734062d13503",
+    "bl-39dad13d-7105-4049-8224-dc3c34fdb1f3",
+    "bl-4ef4d914-da46-4e0f-be78-5219b9547e9f",
+    "bl-7e7c3fdb-4132-487f-aa70-b2cd559cb7f0",
+    "bl-1d32bd54-cf17-4a1f-b235-982d09a36f04",
+    "bl-b8af6601-a8cb-41b5-aef5-ab8a57432dd5"
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+  },
+  {
+   "id": "q08",
+   "category": "phrase",
+   "query": "thirty moves",
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+    "knw-7902acca-604e-409b-8faf-ad85424211d0",
+    "knw-d357b6bb-ad8a-4791-b516-426aea45fa5b",
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+  {
+   "id": "q09",
+   "category": "phrase",
+   "query": "Grandma Lucas",
+   "returned": [
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+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
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+    "kn-6061318f-046b-4935-907d-8eafdce14930",
+    "766de879-f9d0-4a07-b6df-b43ee13763d8",
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+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "art-0f0277a1-4a8e-4645-95dd-fa379976f31c",
+    "kn-f230b362-b201-4402-9833-4160c89ab3d4"
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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",
+    "bl-92acd4eb-0452-4e8e-9f54-f8cd35170d76",
+    "tag-harmonic-framework",
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+   "mrr@10": 0.25
+  },
+  {
+   "id": "q11",
+   "category": "phrase",
+   "query": "Sarah Bishop",
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+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "766de879-f9d0-4a07-b6df-b43ee13763d8",
+    "015644f5-8194-4af0-800d-dd4a0cd71396",
+    "tag-sarah",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "mem-1f32f73a-952c-41bc-96dc-8b8b70d8a7c1",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "mem-a6cb3b8d-d89c-46fc-931d-e90c560783b0",
+    "kn-6061318f-046b-4935-907d-8eafdce14930"
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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-145a0985-2382-400f-a7c5-c335c5e30a72",
+    "bl-5b17bd3b-0c41-46cb-a710-6fa4429692ff",
+    "bl-967536a0-d49d-44fb-8cfb-b31b40bcbfae",
+    "bl-8b58d9bc-352b-4842-a7f8-a6254b5d1e25",
+    "2c56a7a9-5323-4ce4-ba09-35836ba15d54",
+    "bl-39cec462-c80c-4970-a3aa-91fe83053bde"
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+  },
+  {
+   "id": "q13",
+   "category": "phrase",
+   "query": "zero-knowledge encrypted backup",
+   "returned": [
+    "deda48cd-5e1a-46cb-bd43-8016afdb3a8a",
+    "8f3abb0d-77ed-4af3-9f4d-ba62cd198886",
+    "7774a16c-1027-4e3b-a21e-67f1f95a4acd",
+    "?",
+    "bl-ec84b63d-b278-4944-8d7f-4aa7a51c0315",
+    "?",
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+    "?",
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+  },
+  {
+   "id": "q14",
+   "category": "paraphrase",
+   "query": "the elderly relative who passed while he stayed away",
+   "returned": [
+    "cb070131-dfd4-4a38-91d7-22b1bde164d2",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
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+    "66c63082-b4da-4aa1-8fee-848db8a83210",
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+    "mem-a535f205-bc4c-4058-9171-6263c496044a",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "kn-13f60407-7b70-4db1-964f-ea1f8196efbd",
+    "ctx-4a41"
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+  },
+  {
+   "id": "q15",
+   "category": "paraphrase",
+   "query": "a soldier sidelined by illness who refused to quit",
+   "returned": [
+    "b1183213-d659-4759-85d7-5b1f22427fe2",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
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+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "f0eb6b13-909c-4674-91ef-23301d3abc8b",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
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+  },
+  {
+   "id": "q16",
+   "category": "paraphrase",
+   "query": "choosing an uncomfortable fact over a pleasant fiction",
+   "returned": [
+    "mem-ef878e30-5851-4e82-8588-745415108941",
+    "kn-13f60407-7b70-4db1-964f-ea1f8196efbd",
+    "knw-4aebd815-4eaf-49d7-954b-03595f3d48be",
+    "tag-fiction",
+    "knw-8fd9836c-cc39-49df-8d61-babda626cc88",
+    "mem-8d690e9d-a7e9-4062-b2f8-e2064294e463",
+    "knw-e94982a2-358d-4f2f-af31-8ee0fcec07c6",
+    "mem-ce793303-c5a5-4586-a232-a3426edd9ec7",
+    "knw-d357b6bb-ad8a-4791-b516-426aea45fa5b",
+    "mem-443bd012-fc9a-4088-b236-de5157a1ef92"
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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": [
+    "bl-8de20bcf-7149-4f48-b67c-e7f9758fd6e5",
+    "bl-798d135f-3987-4ccd-8de6-70ca2f358337",
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+    "knw-08559f5c-2306-4220-a146-398c74f1643c",
+    "bl-164b520b-c503-49db-89f9-bd2fdf4215f5",
+    "knw-f6ed7d00-bf7d-42ce-9e40-77cf3406e918",
+    "1219277c-1b95-45ec-95a2-07b4a47a4d92",
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+    "bl-79ce4464-5dd6-49bd-9b0c-9803549d0665"
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+  },
+  {
+   "id": "q18",
+   "category": "paraphrase",
+   "query": "if you are able and nobody is coming the job is yours",
+   "returned": [
+    "bl-4476e856-c567-4b49-8ff7-d7dca3e5715e",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "a1000001-0000-0000-0000-000000000010",
+    "a1000001-0000-0000-0000-000000000009",
+    "bl-448bc514-c2f1-4520-a9b1-1f3a73678d26",
+    "a1000001-0000-0000-0000-000000000012",
+    "43098881-e044-482b-8e92-471728a8ba8b",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "mem-e5cc63c0-8701-49d6-855a-e387fe087771",
+    "a1000001-0000-0000-0000-000000000001"
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+  },
+  {
+   "id": "q19",
+   "category": "paraphrase",
+   "query": "learning is the wealth creditors cannot seize",
+   "returned": [
+    "tag-learning",
+    "kn-0bb4f021-56de-4947-a35b-a37209e7ba21",
+    "knw-7902acca-604e-409b-8faf-ad85424211d0",
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+  },
+  {
+   "id": "q20",
+   "category": "paraphrase",
+   "query": "reliability proven by track record not assertion",
+   "returned": [
+    "mem-cde58b77-50d3-4bac-9581-e70a4c02c015",
+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "mem-8d699e2c-ac2a-4742-bb62-b6da00f4b10e",
+    "knw-f671966c-3387-4848-abca-b5deec122e00",
+    "knw-4aebd815-4eaf-49d7-954b-03595f3d48be",
+    "mem-53d6adf0-cd08-4707-a237-daa5e65c7298",
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+   "mrr@10": 0.5
+  },
+  {
+   "id": "q21",
+   "category": "paraphrase",
+   "query": "boundaries that enable instead of confine",
+   "returned": [
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+    "kn-a5b3d0ac-f6a1-49a4-aebb-b8b4cd67fe83",
+    "bl-2515d870-e35e-443b-ba20-5150bbc73fed",
+    "bl-0e8f4880-7b24-43aa-aed9-ad4d9fc73ff8",
+    "project-Source_kn-6f248a50__Add_containment_rules__convergence__location-independence__failure_modes_",
+    "bl-8848929a-a23a-46bc-a2c7-fe3a3bc1cddf",
+    "bl-205141ad-b2a0-4d93-86d0-89eb0723e1bd",
+    "bl-e93858c4-7cac-4b1a-bb62-490790d4c3f3",
+    "bl-34f51ddb-a840-459f-a248-94214f5febb6",
+    "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": [
+    "5a2c118a-87bd-4239-97a7-9e02c5991983",
+    "kn-78db5396-3dbc-4481-bfc7-e4e1422feb1c",
+    "mem-ef878e30-5851-4e82-8588-745415108941",
+    "knw-12b4b913-7a25-4b0d-844c-504c01d6725e",
+    "knw-723551f5-1950-42a3-8b89-b6a06913cef0",
+    "knw-9707256e-ed44-4042-bd88-f90fa514e1cf",
+    "kn-22d77abe-b3c5-42fd-afcd-dcb87d924929",
+    "knw-0087493b-25cd-45b0-bf46-c078c5b49718",
+    "bl-4c5b385e-135a-4663-8521-96af0b491121",
+    "kn-0bb4f021-56de-4947-a35b-a37209e7ba21"
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+   "precision@5": 0.2,
+   "mrr@10": 0.5
+  },
+  {
+   "id": "q23",
+   "category": "paraphrase",
+   "query": "a mind that compounds instead of resetting each day",
+   "returned": [
+    "bl-8dd70cac-866d-4ff2-b9fe-b4b3c5f094bb",
+    "mem-b43f6ef4-2f5a-418d-b5ce-3f21520cf6b8",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "a0edad47-5f77-4fc3-a546-1e85f8c68e77",
+    "a1000001-0000-0000-0000-000000000001",
+    "8cbb60c5-4999-4ec1-8682-2592aedc4249",
+    "96497334-b18f-495c-9228-eeb8182bdc38",
+    "mem-024598a9-ed2e-4eeb-b1e1-5410856ff132",
+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40",
+    "knw-ed33e669-0790-44cb-a036-958d605c6fea"
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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": [
+    "27e1b1a4-ad0b-49d9-812f-fedf43b8aabe",
+    "knw-f9ce17a7-17fc-431f-8f23-695b670ec4fa",
+    "bl-87c93185-b2bf-40af-ae23-3c830c007abf",
+    "knw-2c46cfb4-6d4e-4822-8a1a-7d743c1e4329",
+    "077d064f-3489-4c05-9aca-3782f96b51db",
+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40",
+    "kn-6061318f-046b-4935-907d-8eafdce14930",
+    "knw-920c891f-bb8c-48c4-9afc-018ef12dcdc4",
+    "75e036d3-c170-4e3f-acc2-e456a6850ee2",
+    "a1000001-0000-0000-0000-000000000001"
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q25",
+   "category": "paraphrase",
+   "query": "cheerfulness you arrive at instead of assuming",
+   "returned": [
+    "mem-82158b02-a180-435d-84f0-0b7ce37511b4",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "e4f27651-52c5-43fd-aff3-61d31685b3cd",
+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40",
+    "mem-5624ec9d-62ba-4aba-8a3d-6afec6c09dd4",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "mem-833dbbcd-2400-4594-bb35-93b023049ac0",
+    "a1000001-0000-0000-0000-000000000009",
+    "mem-759e78ca-5394-4244-aa39-1c1468bc5f3e",
+    "kn-13f60407-7b70-4db1-964f-ea1f8196efbd"
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+   "mrr@10": 0.0
+  },
+  {
+   "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,
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+   "recall@5": 1.0,
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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": [
+    "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"
+   ],
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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,
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+   "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,
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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-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,
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+   "recall@5": 0.09090909090909091,
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+   "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,
+   "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": 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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+   "recall@5": 1.0,
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+   "precision@5": 0.2,
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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"
+   ],
+   "n_returned": 10,
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+   "recall@5": 0.0,
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+   "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": 995.5,
+   "error": null,
+   "hit@5": 0.0,
+   "recall@5": 0.0,
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+   "precision@5": 0.0,
+   "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,
+  "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": {
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+    "hit@5": 0.6666666666666666,
+    "recall@5": 0.08857808857808858,
+    "recall@10": 0.23310023310023312,
+    "mrr@10": 0.25
+   },
+   "exact_rare": {
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+    "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": {
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+   "category": "exact_rare",
+   "query": "unjailbreakable",
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+    "bl-b28d7256-6f74-4567-bd90-40d0ef2a6d78",
+    "project-engram",
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+    "project-engram-lang",
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+   "query": "cartabandonedevent",
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+   "query": "pre-apprenticeship",
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+   "category": "exact_rare",
+   "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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+   "query": "clear-eyed",
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+  },
+  {
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+   "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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+  {
+   "id": "q08",
+   "category": "phrase",
+   "query": "thirty moves",
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+    "knw-7902acca-604e-409b-8faf-ad85424211d0",
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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",
+    "bl-92acd4eb-0452-4e8e-9f54-f8cd35170d76",
+    "tag-harmonic-framework",
+    "bl-18a9d1e4-1484-474c-bf6b-c6173212181b"
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+  },
+  {
+   "id": "q11",
+   "category": "phrase",
+   "query": "Sarah Bishop",
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+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "766de879-f9d0-4a07-b6df-b43ee13763d8",
+    "015644f5-8194-4af0-800d-dd4a0cd71396",
+    "tag-sarah",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "mem-1f32f73a-952c-41bc-96dc-8b8b70d8a7c1",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "mem-a6cb3b8d-d89c-46fc-931d-e90c560783b0",
+    "kn-6061318f-046b-4935-907d-8eafdce14930"
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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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+    "2c56a7a9-5323-4ce4-ba09-35836ba15d54",
+    "bl-39cec462-c80c-4970-a3aa-91fe83053bde"
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+  {
+   "id": "q13",
+   "category": "phrase",
+   "query": "zero-knowledge encrypted backup",
+   "returned": [
+    "deda48cd-5e1a-46cb-bd43-8016afdb3a8a",
+    "8f3abb0d-77ed-4af3-9f4d-ba62cd198886",
+    "7774a16c-1027-4e3b-a21e-67f1f95a4acd",
+    "?",
+    "bl-ec84b63d-b278-4944-8d7f-4aa7a51c0315",
+    "?",
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+    "?",
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+  },
+  {
+   "id": "q14",
+   "category": "paraphrase",
+   "query": "the elderly relative who passed while he stayed away",
+   "returned": [
+    "cb070131-dfd4-4a38-91d7-22b1bde164d2",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
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+    "66c63082-b4da-4aa1-8fee-848db8a83210",
+    "kn-6061318f-046b-4935-907d-8eafdce14930",
+    "mem-a535f205-bc4c-4058-9171-6263c496044a",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "kn-13f60407-7b70-4db1-964f-ea1f8196efbd",
+    "ctx-4a41"
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+  },
+  {
+   "id": "q15",
+   "category": "paraphrase",
+   "query": "a soldier sidelined by illness who refused to quit",
+   "returned": [
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+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
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+    "f0eb6b13-909c-4674-91ef-23301d3abc8b",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "30a44d10-2487-420e-bf61-3892e4343c92",
+    "54608b69-78b6-4239-b60f-b8206cfecacc",
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+  },
+  {
+   "id": "q16",
+   "category": "paraphrase",
+   "query": "choosing an uncomfortable fact over a pleasant fiction",
+   "returned": [
+    "mem-ef878e30-5851-4e82-8588-745415108941",
+    "kn-13f60407-7b70-4db1-964f-ea1f8196efbd",
+    "knw-4aebd815-4eaf-49d7-954b-03595f3d48be",
+    "tag-fiction",
+    "knw-8fd9836c-cc39-49df-8d61-babda626cc88",
+    "mem-8d690e9d-a7e9-4062-b2f8-e2064294e463",
+    "knw-e94982a2-358d-4f2f-af31-8ee0fcec07c6",
+    "mem-ce793303-c5a5-4586-a232-a3426edd9ec7",
+    "knw-d357b6bb-ad8a-4791-b516-426aea45fa5b",
+    "mem-443bd012-fc9a-4088-b236-de5157a1ef92"
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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": [
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+    "bl-798d135f-3987-4ccd-8de6-70ca2f358337",
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+    "knw-08559f5c-2306-4220-a146-398c74f1643c",
+    "bl-164b520b-c503-49db-89f9-bd2fdf4215f5",
+    "knw-f6ed7d00-bf7d-42ce-9e40-77cf3406e918",
+    "1219277c-1b95-45ec-95a2-07b4a47a4d92",
+    "knw-920c891f-bb8c-48c4-9afc-018ef12dcdc4",
+    "08f0d1e2-8d0e-42e3-9f0a-8186ae31ec7e",
+    "bl-79ce4464-5dd6-49bd-9b0c-9803549d0665"
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+  },
+  {
+   "id": "q18",
+   "category": "paraphrase",
+   "query": "if you are able and nobody is coming the job is yours",
+   "returned": [
+    "bl-4476e856-c567-4b49-8ff7-d7dca3e5715e",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "a1000001-0000-0000-0000-000000000010",
+    "a1000001-0000-0000-0000-000000000009",
+    "bl-448bc514-c2f1-4520-a9b1-1f3a73678d26",
+    "a1000001-0000-0000-0000-000000000012",
+    "43098881-e044-482b-8e92-471728a8ba8b",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "mem-e5cc63c0-8701-49d6-855a-e387fe087771",
+    "a1000001-0000-0000-0000-000000000001"
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+  },
+  {
+   "id": "q19",
+   "category": "paraphrase",
+   "query": "learning is the wealth creditors cannot seize",
+   "returned": [
+    "tag-learning",
+    "kn-0bb4f021-56de-4947-a35b-a37209e7ba21",
+    "knw-7902acca-604e-409b-8faf-ad85424211d0",
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+   "mrr@10": 0.5
+  },
+  {
+   "id": "q20",
+   "category": "paraphrase",
+   "query": "reliability proven by track record not assertion",
+   "returned": [
+    "mem-cde58b77-50d3-4bac-9581-e70a4c02c015",
+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "mem-8d699e2c-ac2a-4742-bb62-b6da00f4b10e",
+    "knw-f671966c-3387-4848-abca-b5deec122e00",
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+    "mem-53d6adf0-cd08-4707-a237-daa5e65c7298",
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+  {
+   "id": "q21",
+   "category": "paraphrase",
+   "query": "boundaries that enable instead of confine",
+   "returned": [
+    "bl-8dd70cac-866d-4ff2-b9fe-b4b3c5f094bb",
+    "kn-a5b3d0ac-f6a1-49a4-aebb-b8b4cd67fe83",
+    "bl-2515d870-e35e-443b-ba20-5150bbc73fed",
+    "bl-0e8f4880-7b24-43aa-aed9-ad4d9fc73ff8",
+    "project-Source_kn-6f248a50__Add_containment_rules__convergence__location-independence__failure_modes_",
+    "bl-8848929a-a23a-46bc-a2c7-fe3a3bc1cddf",
+    "bl-205141ad-b2a0-4d93-86d0-89eb0723e1bd",
+    "bl-e93858c4-7cac-4b1a-bb62-490790d4c3f3",
+    "bl-34f51ddb-a840-459f-a248-94214f5febb6",
+    "bl-286b562a-5299-40e0-a32a-afa9cbdfe995"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1359.1,
+   "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": [
+    "5a2c118a-87bd-4239-97a7-9e02c5991983",
+    "kn-78db5396-3dbc-4481-bfc7-e4e1422feb1c",
+    "mem-ef878e30-5851-4e82-8588-745415108941",
+    "knw-12b4b913-7a25-4b0d-844c-504c01d6725e",
+    "knw-723551f5-1950-42a3-8b89-b6a06913cef0",
+    "knw-9707256e-ed44-4042-bd88-f90fa514e1cf",
+    "kn-22d77abe-b3c5-42fd-afcd-dcb87d924929",
+    "knw-0087493b-25cd-45b0-bf46-c078c5b49718",
+    "bl-4c5b385e-135a-4663-8521-96af0b491121",
+    "kn-0bb4f021-56de-4947-a35b-a37209e7ba21"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1620.0,
+   "error": null,
+   "hit@5": 1.0,
+   "recall@5": 1.0,
+   "recall@10": 1.0,
+   "precision@5": 0.2,
+   "mrr@10": 0.5
+  },
+  {
+   "id": "q23",
+   "category": "paraphrase",
+   "query": "a mind that compounds instead of resetting each day",
+   "returned": [
+    "bl-8dd70cac-866d-4ff2-b9fe-b4b3c5f094bb",
+    "mem-b43f6ef4-2f5a-418d-b5ce-3f21520cf6b8",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "a0edad47-5f77-4fc3-a546-1e85f8c68e77",
+    "a1000001-0000-0000-0000-000000000001",
+    "8cbb60c5-4999-4ec1-8682-2592aedc4249",
+    "96497334-b18f-495c-9228-eeb8182bdc38",
+    "mem-024598a9-ed2e-4eeb-b1e1-5410856ff132",
+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40",
+    "knw-ed33e669-0790-44cb-a036-958d605c6fea"
+   ],
+   "n_returned": 10,
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+   "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": [
+    "27e1b1a4-ad0b-49d9-812f-fedf43b8aabe",
+    "knw-f9ce17a7-17fc-431f-8f23-695b670ec4fa",
+    "bl-87c93185-b2bf-40af-ae23-3c830c007abf",
+    "knw-2c46cfb4-6d4e-4822-8a1a-7d743c1e4329",
+    "077d064f-3489-4c05-9aca-3782f96b51db",
+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40",
+    "kn-6061318f-046b-4935-907d-8eafdce14930",
+    "knw-920c891f-bb8c-48c4-9afc-018ef12dcdc4",
+    "75e036d3-c170-4e3f-acc2-e456a6850ee2",
+    "a1000001-0000-0000-0000-000000000001"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1516.7,
+   "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": [
+    "mem-82158b02-a180-435d-84f0-0b7ce37511b4",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "e4f27651-52c5-43fd-aff3-61d31685b3cd",
+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40",
+    "mem-5624ec9d-62ba-4aba-8a3d-6afec6c09dd4",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "mem-833dbbcd-2400-4594-bb35-93b023049ac0",
+    "a1000001-0000-0000-0000-000000000009",
+    "mem-759e78ca-5394-4244-aa39-1c1468bc5f3e",
+    "kn-13f60407-7b70-4db1-964f-ea1f8196efbd"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1237.3,
+   "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": [
+    "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": 1337.0,
+   "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"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1433.6,
+   "error": null,
+   "hit@5": 1.0,
+   "recall@5": 0.18181818181818182,
+   "recall@10": 0.45454545454545453,
+   "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,
+   "latency_ms": 1114.9,
+   "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": 1184.4,
+   "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": 1185.7,
+   "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": 1199.5,
+   "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-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": 1422.0,
+   "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": 703.8,
+   "error": null,
+   "clean": true,
+   "false_positives": 0
+  },
+  {
+   "id": "q34",
+   "category": "nonsense",
+   "query": "flarnbistle quommetry",
+   "returned": [],
+   "n_returned": 0,
+   "latency_ms": 488.0,
+   "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": 720.7,
+   "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"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1301.5,
+   "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",
+    "7ac62daa-2eac-4c7a-a97e-e4203fc1b57b"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1651.7,
+   "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": 1021.6,
+   "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": 5
+  }
+ ]
+}

tools/retrieval-eval/results-execfilter.json

@@ -0,0 +1,959 @@
+{
+ "label": "execfilter",
+ "soul_binary": "/private/tmp/claude-501/-Users-timlingo/82369039-a20e-4b5a-8a5e-28234a57b996/scratchpad/soul-execfilter",
+ "soul_md5": "1b2dbc92a1b96327c54b7fbd8d448336",
+ "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-bm25lex/tools/retrieval-eval/gold_set.json",
+ "limit": 10,
+ "port": 7931,
+ "wall_clock_s": 50.5,
+ "child_pid": 91170,
+ "child_confirmed_dead": true,
+ "aggregate": {
+  "n_queries": 38,
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+ "rows": [
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+   "id": "q01",
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+   "query": "unjailbreakable",
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+  {
+   "id": "q03",
+   "category": "exact_rare",
+   "query": "cartabandonedevent",
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+  {
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+   "query": "pre-apprenticeship",
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+  {
+   "id": "q05",
+   "category": "exact_rare",
+   "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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+   "id": "q06",
+   "category": "exact_rare",
+   "query": "clear-eyed",
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+  },
+  {
+   "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_",
+    "bl-79028eed-c330-4724-9402-734062d13503",
+    "bl-39dad13d-7105-4049-8224-dc3c34fdb1f3",
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+  {
+   "id": "q08",
+   "category": "phrase",
+   "query": "thirty moves",
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+    "knw-d357b6bb-ad8a-4791-b516-426aea45fa5b",
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+  },
+  {
+   "id": "q09",
+   "category": "phrase",
+   "query": "Grandma Lucas",
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+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "kn-6061318f-046b-4935-907d-8eafdce14930",
+    "766de879-f9d0-4a07-b6df-b43ee13763d8",
+    "kn-0bb4f021-56de-4947-a35b-a37209e7ba21",
+    "bl-33ecccc2-e37f-43db-91b3-c2a86f08aaac",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "art-0f0277a1-4a8e-4645-95dd-fa379976f31c",
+    "kn-f230b362-b201-4402-9833-4160c89ab3d4"
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+   "mrr@10": 1.0
+  },
+  {
+   "id": "q10",
+   "category": "phrase",
+   "query": "Directed Harmonic",
+   "returned": [
+    "bl-dcee1887-34c4-4ffa-9119-1e291685ba08",
+    "bl-798d135f-3987-4ccd-8de6-70ca2f358337",
+    "mem-7eeacad7-d7c2-4c2b-8348-19a59aa6dbaf",
+    "bl-680b24a9-edc3-4a9d-847a-bff0b46b568c",
+    "tag-harmonic-design",
+    "bl-92acd4eb-0452-4e8e-9f54-f8cd35170d76",
+    "tag-harmonic-framework",
+    "bl-18a9d1e4-1484-474c-bf6b-c6173212181b",
+    "project-harmonic-framework",
+    "project-harmonic-framework_com"
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+   "mrr@10": 0.3333333333333333
+  },
+  {
+   "id": "q11",
+   "category": "phrase",
+   "query": "Sarah Bishop",
+   "returned": [
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+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "766de879-f9d0-4a07-b6df-b43ee13763d8",
+    "015644f5-8194-4af0-800d-dd4a0cd71396",
+    "tag-sarah",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "mem-1f32f73a-952c-41bc-96dc-8b8b70d8a7c1",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "mem-a6cb3b8d-d89c-46fc-931d-e90c560783b0",
+    "kn-6061318f-046b-4935-907d-8eafdce14930"
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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",
+    "mem-82b93b21-a865-410f-9ec1-fc54121d9bb5",
+    "bl-6f99e111-7055-4635-9831-a489747ce418",
+    "bl-145a0985-2382-400f-a7c5-c335c5e30a72",
+    "bl-967536a0-d49d-44fb-8cfb-b31b40bcbfae",
+    "bl-5b17bd3b-0c41-46cb-a710-6fa4429692ff",
+    "bl-8b58d9bc-352b-4842-a7f8-a6254b5d1e25",
+    "2c56a7a9-5323-4ce4-ba09-35836ba15d54",
+    "bl-39cec462-c80c-4970-a3aa-91fe83053bde"
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+   "precision@5": 0.6,
+   "mrr@10": 1.0
+  },
+  {
+   "id": "q13",
+   "category": "phrase",
+   "query": "zero-knowledge encrypted backup",
+   "returned": [
+    "deda48cd-5e1a-46cb-bd43-8016afdb3a8a",
+    "7774a16c-1027-4e3b-a21e-67f1f95a4acd",
+    "bl-ec84b63d-b278-4944-8d7f-4aa7a51c0315",
+    "830ca37a-d334-4e41-ba89-64893dc8d628",
+    "ce9636dc-85a5-4dae-9e07-74ea2fcc6307",
+    "mem-fb44a2fc-7405-41ff-87b3-84643ac07313",
+    "mem-a3c97012-5fa3-4915-a839-2c75c72005e0",
+    "8f3abb0d-77ed-4af3-9f4d-ba62cd198886",
+    "mem-ce88adf9-3f3c-47ac-a7d3-83af7b290e68",
+    "bl-e20944e5-f4a6-44a0-91b1-73d04ebed120"
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+   "mrr@10": 1.0
+  },
+  {
+   "id": "q14",
+   "category": "paraphrase",
+   "query": "the elderly relative who passed while he stayed away",
+   "returned": [
+    "cb070131-dfd4-4a38-91d7-22b1bde164d2",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "knw-d788a210-613b-4c49-9486-88bbc9d4716f",
+    "kn-0bb4f021-56de-4947-a35b-a37209e7ba21",
+    "mem-a535f205-bc4c-4058-9171-6263c496044a",
+    "kn-6061318f-046b-4935-907d-8eafdce14930",
+    "kn-13f60407-7b70-4db1-964f-ea1f8196efbd",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "mem-2265c223-9e19-47b5-b7ba-5e9c2ce1f22c",
+    "knw-729fc901-8335-44c4-9f3a-b150b4aa0915"
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q15",
+   "category": "paraphrase",
+   "query": "a soldier sidelined by illness who refused to quit",
+   "returned": [
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "54608b69-78b6-4239-b60f-b8206cfecacc",
+    "kn-13f60407-7b70-4db1-964f-ea1f8196efbd",
+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40",
+    "kn-0bb4f021-56de-4947-a35b-a37209e7ba21",
+    "kn-a5b3d0ac-f6a1-49a4-aebb-b8b4cd67fe83",
+    "kn-6061318f-046b-4935-907d-8eafdce14930",
+    "kn-78db5396-3dbc-4481-bfc7-e4e1422feb1c"
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q16",
+   "category": "paraphrase",
+   "query": "choosing an uncomfortable fact over a pleasant fiction",
+   "returned": [
+    "mem-ef878e30-5851-4e82-8588-745415108941",
+    "knw-4aebd815-4eaf-49d7-954b-03595f3d48be",
+    "mem-16efddd1-c43d-4a42-9d78-f54fb82bd277",
+    "knw-8fd9836c-cc39-49df-8d61-babda626cc88",
+    "knw-6fae4d4b-dbe8-45c5-8bd4-21ffd5caa240",
+    "knw-e94982a2-358d-4f2f-af31-8ee0fcec07c6",
+    "knw-d357b6bb-ad8a-4791-b516-426aea45fa5b",
+    "knw-f671966c-3387-4848-abca-b5deec122e00",
+    "knw-ed33e669-0790-44cb-a036-958d605c6fea",
+    "knw-723551f5-1950-42a3-8b89-b6a06913cef0"
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q17",
+   "category": "paraphrase",
+   "query": "a tight payload beats a bloated one",
+   "returned": [
+    "bl-680b24a9-edc3-4a9d-847a-bff0b46b568c",
+    "bl-798d135f-3987-4ccd-8de6-70ca2f358337",
+    "kn-2b961d24-7fb9-47c7-9515-e45a24dce39d",
+    "knw-08559f5c-2306-4220-a146-398c74f1643c",
+    "kn-0710e5b4-799d-4a0e-afd3-62d43b38ea37",
+    "knw-f6ed7d00-bf7d-42ce-9e40-77cf3406e918",
+    "knw-723551f5-1950-42a3-8b89-b6a06913cef0",
+    "knw-920c891f-bb8c-48c4-9afc-018ef12dcdc4",
+    "kn-c72bb6db-bd1e-4d37-bded-0399194496f6",
+    "bl-79ce4464-5dd6-49bd-9b0c-9803549d0665"
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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": [
+    "bl-4476e856-c567-4b49-8ff7-d7dca3e5715e",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "a1000001-0000-0000-0000-000000000010",
+    "a1000001-0000-0000-0000-000000000009",
+    "bl-448bc514-c2f1-4520-a9b1-1f3a73678d26",
+    "a1000001-0000-0000-0000-000000000012",
+    "43098881-e044-482b-8e92-471728a8ba8b",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "mem-e5cc63c0-8701-49d6-855a-e387fe087771",
+    "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-7902acca-604e-409b-8faf-ad85424211d0",
+    "kn-0bb4f021-56de-4947-a35b-a37209e7ba21",
+    "kn-f230b362-b201-4402-9833-4160c89ab3d4",
+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40",
+    "knw-ed33e669-0790-44cb-a036-958d605c6fea",
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+  {
+   "id": "q20",
+   "category": "paraphrase",
+   "query": "reliability proven by track record not assertion",
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+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
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+  },
+  {
+   "id": "q21",
+   "category": "paraphrase",
+   "query": "boundaries that enable instead of confine",
+   "returned": [
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+    "bl-2515d870-e35e-443b-ba20-5150bbc73fed",
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+    "bl-8848929a-a23a-46bc-a2c7-fe3a3bc1cddf",
+    "bl-205141ad-b2a0-4d93-86d0-89eb0723e1bd",
+    "bl-e93858c4-7cac-4b1a-bb62-490790d4c3f3",
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+  {
+   "id": "q22",
+   "category": "paraphrase",
+   "query": "what shifts tells you where to cut a system apart",
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+    "kn-78db5396-3dbc-4481-bfc7-e4e1422feb1c",
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+  {
+   "id": "q23",
+   "category": "paraphrase",
+   "query": "a mind that compounds instead of resetting each day",
+   "returned": [
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+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
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+    "kn-78db5396-3dbc-4481-bfc7-e4e1422feb1c",
+    "d0434bdc-c75d-40ef-a989-bba4fa271a7c",
+    "ctx-4a41"
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+  },
+  {
+   "id": "q24",
+   "category": "paraphrase",
+   "query": "loved for the unedited self and not the polished exterior",
+   "returned": [
+    "bl-87c93185-b2bf-40af-ae23-3c830c007abf",
+    "knw-f9ce17a7-17fc-431f-8f23-695b670ec4fa",
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+    "a1000001-0000-0000-0000-000000000001"
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+  },
+  {
+   "id": "q25",
+   "category": "paraphrase",
+   "query": "cheerfulness you arrive at instead of assuming",
+   "returned": [
+    "mem-82158b02-a180-435d-84f0-0b7ce37511b4",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "e4f27651-52c5-43fd-aff3-61d31685b3cd",
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+    "mem-5624ec9d-62ba-4aba-8a3d-6afec6c09dd4",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
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+    "a1000001-0000-0000-0000-000000000009",
+    "mem-154c3ec1-061c-4314-9e5f-50dc9b9422bc",
+    "kn-13f60407-7b70-4db1-964f-ea1f8196efbd"
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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-f230b362-b201-4402-9833-4160c89ab3d4",
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+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "mem-b99efff0-00e6-40c8-9c5b-730330eef33b",
+    "kn-5b606390-a52d-4ca2-8e0e-eba141d13440",
+    "kn-6061318f-046b-4935-907d-8eafdce14930",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
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+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40"
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+  },
+  {
+   "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",
+    "knw-f671966c-3387-4848-abca-b5deec122e00",
+    "kn-e0423482-cfa5-4796-8689-8495c93b66bc",
+    "kn-78db5396-3dbc-4481-bfc7-e4e1422feb1c",
+    "kn-6061318f-046b-4935-907d-8eafdce14930"
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+  },
+  {
+   "id": "q28",
+   "category": "associative",
+   "query": "Marines hernia sepsis medical ward",
+   "returned": [
+    "bl-33ecccc2-e37f-43db-91b3-c2a86f08aaac",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "015644f5-8194-4af0-800d-dd4a0cd71396",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "kn-f230b362-b201-4402-9833-4160c89ab3d4",
+    "kn-78db5396-3dbc-4481-bfc7-e4e1422feb1c",
+    "kn-0bb4f021-56de-4947-a35b-a37209e7ba21",
+    "kn-a5b3d0ac-f6a1-49a4-aebb-b8b4cd67fe83"
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+   "mrr@10": 0.5
+  },
+  {
+   "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",
+    "project-trailer-park-paladins",
+    "015644f5-8194-4af0-800d-dd4a0cd71396",
+    "knw-528dbc37-eabc-4b75-a7a5-65bf38d6018a",
+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40",
+    "kn-78db5396-3dbc-4481-bfc7-e4e1422feb1c",
+    "kn-6061318f-046b-4935-907d-8eafdce14930"
+   ],
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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",
+    "kn-b36902cc-0b05-44ba-9aa7-800e5dea9ca9",
+    "bl-bea7473c-c687-414c-9c0b-00c509a616c1",
+    "bl-fc6fcb0b-9e4b-40bf-8e88-dbfe4e27c31a",
+    "kn-6061318f-046b-4935-907d-8eafdce14930",
+    "mem-ab34c2f7-3243-424b-affa-25555f6cf9cc",
+    "015644f5-8194-4af0-800d-dd4a0cd71396"
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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",
+    "bl-2b00aeb0-c0fa-4a9f-8f30-4207e98b3d52",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "kn-5b606390-a52d-4ca2-8e0e-eba141d13440",
+    "knw-723551f5-1950-42a3-8b89-b6a06913cef0",
+    "knw-8fd9836c-cc39-49df-8d61-babda626cc88",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "bl-9773fd67-2ac8-42cd-bea0-702e85f4565e",
+    "knw-920c891f-bb8c-48c4-9afc-018ef12dcdc4"
+   ],
+   "n_returned": 10,
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+   "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"
+   ],
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+  },
+  {
+   "id": "q33",
+   "category": "nonsense",
+   "query": "zqxjvw plimforth grebulon",
+   "returned": [],
+   "n_returned": 0,
+   "latency_ms": 730.1,
+   "error": null,
+   "clean": true,
+   "false_positives": 0
+  },
+  {
+   "id": "q34",
+   "category": "nonsense",
+   "query": "flarnbistle quommetry",
+   "returned": [],
+   "n_returned": 0,
+   "latency_ms": 501.9,
+   "error": null,
+   "clean": true,
+   "false_positives": 0
+  },
+  {
+   "id": "q35",
+   "category": "nonsense",
+   "query": "xxqzzt vurblenacht throom",
+   "returned": [
+    "bl-4476e856-c567-4b49-8ff7-d7dca3e5715e",
+    "knw-6b48dce2-f21c-452a-9db5-4e6aa61c87ca",
+    "knw-920c891f-bb8c-48c4-9afc-018ef12dcdc4",
+    "8cbb60c5-4999-4ec1-8682-2592aedc4249",
+    "knw-723551f5-1950-42a3-8b89-b6a06913cef0",
+    "knw-08559f5c-2306-4220-a146-398c74f1643c",
+    "015644f5-8194-4af0-800d-dd4a0cd71396",
+    "knw-f9ce17a7-17fc-431f-8f23-695b670ec4fa",
+    "knw-0087493b-25cd-45b0-bf46-c078c5b49718",
+    "kn-efeb4a5b-5aff-4759-8a97-7233099be6ee"
+   ],
+   "n_returned": 10,
+   "latency_ms": 738.2,
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+   "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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+   "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",
+    "015644f5-8194-4af0-800d-dd4a0cd71396",
+    "13705072-4515-4124-963d-083af490494f",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "a1000001-0000-0000-0000-000000000002",
+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40",
+    "7ac62daa-2eac-4c7a-a97e-e4203fc1b57b",
+    "kn-5b606390-a52d-4ca2-8e0e-eba141d13440",
+    "2aedba58-a4a3-4d14-b0db-fb59f976803f",
+    "a1000001-0000-0000-0000-000000000003"
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+}

tools/retrieval-eval/results-execfilter2.json

@@ -0,0 +1,959 @@
+{
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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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+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
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+  {
+   "id": "q19",
+   "category": "paraphrase",
+   "query": "learning is the wealth creditors cannot seize",
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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",
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+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40",
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+    "mem-8d699e2c-ac2a-4742-bb62-b6da00f4b10e",
+    "knw-f671966c-3387-4848-abca-b5deec122e00",
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+  {
+   "id": "q21",
+   "category": "paraphrase",
+   "query": "boundaries that enable instead of confine",
+   "returned": [
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+    "kn-a5b3d0ac-f6a1-49a4-aebb-b8b4cd67fe83",
+    "bl-2515d870-e35e-443b-ba20-5150bbc73fed",
+    "bl-0e8f4880-7b24-43aa-aed9-ad4d9fc73ff8",
+    "project-Source_kn-6f248a50__Add_containment_rules__convergence__location-independence__failure_modes_",
+    "bl-8848929a-a23a-46bc-a2c7-fe3a3bc1cddf",
+    "bl-205141ad-b2a0-4d93-86d0-89eb0723e1bd",
+    "bl-e93858c4-7cac-4b1a-bb62-490790d4c3f3",
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+  {
+   "id": "q22",
+   "category": "paraphrase",
+   "query": "what shifts tells you where to cut a system apart",
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+    "kn-78db5396-3dbc-4481-bfc7-e4e1422feb1c",
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+    "kn-22d77abe-b3c5-42fd-afcd-dcb87d924929",
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+  },
+  {
+   "id": "q23",
+   "category": "paraphrase",
+   "query": "a mind that compounds instead of resetting each day",
+   "returned": [
+    "bl-8dd70cac-866d-4ff2-b9fe-b4b3c5f094bb",
+    "mem-b43f6ef4-2f5a-418d-b5ce-3f21520cf6b8",
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+    "a1000001-0000-0000-0000-000000000001",
+    "8cbb60c5-4999-4ec1-8682-2592aedc4249",
+    "96497334-b18f-495c-9228-eeb8182bdc38",
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+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40",
+    "knw-ed33e669-0790-44cb-a036-958d605c6fea"
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+  },
+  {
+   "id": "q24",
+   "category": "paraphrase",
+   "query": "loved for the unedited self and not the polished exterior",
+   "returned": [
+    "bl-87c93185-b2bf-40af-ae23-3c830c007abf",
+    "knw-f9ce17a7-17fc-431f-8f23-695b670ec4fa",
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+    "kn-66a21179-2adc-4b19-a109-880cf4674d7d",
+    "a1000001-0000-0000-0000-000000000001"
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+  },
+  {
+   "id": "q25",
+   "category": "paraphrase",
+   "query": "cheerfulness you arrive at instead of assuming",
+   "returned": [
+    "mem-82158b02-a180-435d-84f0-0b7ce37511b4",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "e4f27651-52c5-43fd-aff3-61d31685b3cd",
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+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
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+    "a1000001-0000-0000-0000-000000000009",
+    "mem-154c3ec1-061c-4314-9e5f-50dc9b9422bc",
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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",
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+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
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+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "kn-5b606390-a52d-4ca2-8e0e-eba141d13440",
+    "kn-0bb4f021-56de-4947-a35b-a37209e7ba21"
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+   "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",
+    "knw-f671966c-3387-4848-abca-b5deec122e00",
+    "kn-e0423482-cfa5-4796-8689-8495c93b66bc",
+    "kn-78db5396-3dbc-4481-bfc7-e4e1422feb1c",
+    "kn-6061318f-046b-4935-907d-8eafdce14930"
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+   "mrr@10": 0.5
+  },
+  {
+   "id": "q28",
+   "category": "associative",
+   "query": "Marines hernia sepsis medical ward",
+   "returned": [
+    "bl-33ecccc2-e37f-43db-91b3-c2a86f08aaac",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "kn-58874a74-b96f-4883-9e08-45707f4bd3ee",
+    "015644f5-8194-4af0-800d-dd4a0cd71396",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e",
+    "kn-a99cefe3-5e83-4050-98d8-6c69f57c7c71",
+    "kn-f230b362-b201-4402-9833-4160c89ab3d4",
+    "kn-78db5396-3dbc-4481-bfc7-e4e1422feb1c",
+    "kn-0bb4f021-56de-4947-a35b-a37209e7ba21",
+    "kn-a5b3d0ac-f6a1-49a4-aebb-b8b4cd67fe83"
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+   "mrr@10": 0.5
+  },
+  {
+   "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",
+    "project-trailer-park-paladins",
+    "015644f5-8194-4af0-800d-dd4a0cd71396",
+    "knw-528dbc37-eabc-4b75-a7a5-65bf38d6018a",
+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40",
+    "kn-78db5396-3dbc-4481-bfc7-e4e1422feb1c",
+    "kn-6061318f-046b-4935-907d-8eafdce14930"
+   ],
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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",
+    "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": 1205.9,
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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-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",
+    "knw-8fd9836c-cc39-49df-8d61-babda626cc88",
+    "knw-d357b6bb-ad8a-4791-b516-426aea45fa5b",
+    "kn-db9f141b-dbe3-4037-92e0-4bb9be0e5e6e"
+   ],
+   "n_returned": 10,
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+   "recall@5": 0.09090909090909091,
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+   "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": 1439.5,
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+   "mrr@10": 0.0
+  },
+  {
+   "id": "q33",
+   "category": "nonsense",
+   "query": "zqxjvw plimforth grebulon",
+   "returned": [],
+   "n_returned": 0,
+   "latency_ms": 723.6,
+   "error": null,
+   "clean": true,
+   "false_positives": 0
+  },
+  {
+   "id": "q34",
+   "category": "nonsense",
+   "query": "flarnbistle quommetry",
+   "returned": [],
+   "n_returned": 0,
+   "latency_ms": 505.6,
+   "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",
+    "?m?\\}Q??6??",
+    "knw-723551f5-1950-42a3-8b89-b6a06913cef0",
+    "?m?\\}Q??6??",
+    "knw-08559f5c-2306-4220-a146-398c74f1643c"
+   ],
+   "n_returned": 10,
+   "latency_ms": 741.2,
+   "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__",
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+}

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

@@ -0,0 +1,957 @@
+{
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+   "id": "q17",
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+   "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",
+    "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"
+   ],
+   "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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+   "n_returned": 9,
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+   "precision@5": 0.2,
+   "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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+   "precision@5": 0.2,
+   "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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+   "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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+   "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?",
+    "kn-78db5396-3dbc-4481-bfc7-e4e1422feb1c",
+    "kn-9397c74b-35f3-4428-b4b0-5123353bbcd1",
+    "kn-0bb4f021-56de-4947-a35b-a37209e7ba21",
+    "knw-9e74ee95-ba7d-49b1-9262-977eae9729d1",
+    "kn-6061318f-046b-4935-907d-8eafdce14930",
+    "kn-f8974b26-78a6-4aad-b893-19a73b20013d",
+    "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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+   "n_returned": 10,
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+   "error": null,
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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",
+    "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"
+   ],
+   "n_returned": 10,
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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"
+   ],
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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",
+    "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"
+   ],
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+   "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",
+    "bl-2515d870-e35e-443b-ba20-5150bbc73fed",
+    "8cbb60c5-4999-4ec1-8682-2592aedc4249",
+    "kn-6f248a50-355b-47bb-aec8-e0e646a9b077",
+    "ctx-bb74",
+    "bl-0fac287f-f4c0-4f15-bc4d-ff7f8a7af3ae",
+    "bl-8c2d5f51-3ccd-4c2e-848a-eb60d90a3b98"
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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",
+    "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",
+    "knw-9e74ee95-ba7d-49b1-9262-977eae9729d1",
+    "knw-d357b6bb-ad8a-4791-b516-426aea45fa5b"
+   ],
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+   "precision@5": 0.2,
+   "mrr@10": 0.25
+  },
+  {
+   "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"
+   ],
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+   "precision@5": 0.0,
+   "mrr@10": 0.16666666666666666
+  },
+  {
+   "id": "q33",
+   "category": "nonsense",
+   "query": "zqxjvw plimforth grebulon",
+   "returned": [],
+   "n_returned": 0,
+   "latency_ms": 757.4,
+   "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??",
+    "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": 764.0,
+   "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": 1340.6,
+   "error": null,
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+   "recall@5": 1.0,
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+   "outranks": true,
+   "rank_correct": 2,
+   "rank_stale": 10
+  },
+  {
+   "id": "q37",
+   "category": "superseded",
+   "query": "how many provisional patents does Will actually have",
+   "returned": [
+    "? ?}&?#??X\b",
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+    "%???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",
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+    "?ǚ?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?",
+    "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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+   "n_returned": 9,
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+   "error": null,
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+   "precision@5": 0.2,
+   "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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+   "precision@5": 0.2,
+   "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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+  },
+  {
+   "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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+   "n_returned": 10,
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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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+   "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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+   "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",
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+    "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",
+    "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"
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+   "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",
+    "bl-2515d870-e35e-443b-ba20-5150bbc73fed",
+    "8cbb60c5-4999-4ec1-8682-2592aedc4249",
+    "kn-6f248a50-355b-47bb-aec8-e0e646a9b077",
+    "ctx-bb74",
+    "bl-0fac287f-f4c0-4f15-bc4d-ff7f8a7af3ae",
+    "bl-8c2d5f51-3ccd-4c2e-848a-eb60d90a3b98"
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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",
+    "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",
+    "knw-9e74ee95-ba7d-49b1-9262-977eae9729d1",
+    "knw-d357b6bb-ad8a-4791-b516-426aea45fa5b"
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+   "mrr@10": 0.25
+  },
+  {
+   "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"
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+   "mrr@10": 0.16666666666666666
+  },
+  {
+   "id": "q33",
+   "category": "nonsense",
+   "query": "zqxjvw plimforth grebulon",
+   "returned": [],
+   "n_returned": 0,
+   "latency_ms": 756.0,
+   "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??",
+    "knw-723551f5-1950-42a3-8b89-b6a06913cef0",
+    "art-ddfcd045-2c3b-4a1e-9966-fec5ce44e1dd"
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+   "n_returned": 10,
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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",
+    "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": 1329.3,
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+   "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",
+    "6de314bf-5c4c-4cfc-871f-fa2e422d45e6",
+    "? ?}&?#??X\b",
+    "527ecb25-2587-47eb-8269-73be2431abd4",
+    "kn-eb1b9e18-3dc6-4b9b-9cc6-86e0ae6b6be8",
+    "? ?}&?#??X\b",
+    "3cf706a1-3825-45d8-b0a9-06cae6cdf5b8",
+    "kn-5de5a9ac-fd15-45ab-bf18-77566781cf40",
+    "? ?}&?#??X\b"
+   ],
+   "n_returned": 10,
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+   "outranks": true,
+   "rank_correct": 8,
+   "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",
+    "bl-c8c19362-430b-4817-9cf4-9e85e0099c64",
+    "7?e?7???\f3?",
+    "mem-101e81b4-8097-4749-8d8d-7bb66de34517",
+    "ctx-3a55",
+    "? ?}&?#??X\b",
+    "4509ed62-9fb2-48b8-9038-ac569fca9604",
+    "bl-4f7b651b-6b33-449c-8a3b-cfce12ce984b",
+    "%???2??jH??"
+   ],
+   "n_returned": 10,
+   "latency_ms": 1040.0,
+   "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/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/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

@@ -7387,6 +7387,48 @@ static int engram_node_match_score(const EngramNode* n,
     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(n->content, toks[t]) ||
+            istr_contains(n->label,   toks[t]) ||
+            istr_contains(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
@@ -7406,7 +7448,12 @@ static double eg_sem_term(const EngramNode* n, const float* qv, int32_t qdim) {
  * (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; } EngramRankEntry;
+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;
@@ -7416,6 +7463,21 @@ 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. */
@@ -7531,8 +7593,30 @@ static int eg_assoc_excluded(const EngramNode* n) {
  * 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;
@@ -7553,6 +7637,14 @@ static int64_t engram_assoc_leg(EngramStore* g,
         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) {
@@ -7585,6 +7677,7 @@ static int64_t engram_assoc_leg(EngramStore* g,
         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;
@@ -7603,11 +7696,15 @@ static int64_t engram_assoc_leg(EngramStore* g,
  * 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. */
+/* `no` is the count ALREADY in `out` — the promoted pass fills the head, the
+ * suppressed pass appends behind it and must dedup against the whole prefix
+ * (the same node can be promoted in one leg and suppressed in another, since
+ * its background activation differs per leg). (2026-08-07, claim 44/45) */
 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;
+                                  int64_t lim, int64_t* out, int64_t no) {
+    int64_t li = 0, si = 0, ai = 0;
     while (no < lim && (li < nL || si < nS || ai < nA)) {
         if (li < nL) {
             int dup = 0;
@@ -9498,6 +9595,47 @@ el_val_t engram_get_node_by_label(el_val_t label) {
     return el_wrap_str(el_strdup("{}"));
 }
 
+/* ── Layer 2: the executive filter, on the recall read path (claims 44/45) ──
+ *
+ * 06-claims.md claim 44 (verbatim): "execute a first activation pass that
+ * propagates spreading activation from query-matched seed node records ...
+ * WITHOUT ANY THRESHOLD FILTERING, recording a background activation score for
+ * every reachable node record; and execute a second executive filter pass that
+ * computes a working memory weight for each background-activated node record by
+ * multiplying the background activation score by a goal-state attentional bias
+ * derived from the current query and by the node record's confidence value ...
+ * wherein context compilation uses only node records whose working memory
+ * weight exceeds a per-type threshold, and node records that do not exceed the
+ * threshold retain their background activation scores and are not discarded."
+ * Claim 45 keeps the un-promoted field available to callers.
+ * 05-detailed-description l.221: "Results are sorted with promoted nodes first
+ * ... followed by background-only nodes."
+ *
+ * This pass exists in engram_activate and NOWHERE on the route the app calls.
+ * /api/neuron/recall reaches engram_search_json, whose three legs each get a
+ * fixed share of the output slots by rotation — so on a query where a leg is
+ * structurally incapable of being right, that leg still consumes its slots.
+ * The promotion gate is Will's own answer to that: a candidate that does not
+ * clear its per-type threshold is not discarded, it is moved behind the ones
+ * that do, and the freed slots go to whichever leg still has promoted material.
+ *
+ * ENGRAM_WM_LEG_SCAN bounds the per-leg work: only the head of each already
+ * sorted leg can reach a result slot at any sane limit.
+ */
+#define ENGRAM_WM_LEG_SCAN 64
+
+static int eg_wm_promote(const EngramNode* n, const char* q, double bg,
+                         double* wm_out) {
+    /* Same product engram_activate's pass 2 computes (l.8519), minus the
+     * inhibitory / inhibition-of-return terms, which need activation state
+     * this read path does not carry. */
+    double bias = engram_goal_bias(n, q);
+    double impf = (n->importance > 0.0) ? (0.5 + n->importance) : 1.0;
+    double wm   = bg * bias * n->confidence * impf;
+    if (wm_out) *wm_out = wm;
+    return wm > engram_type_threshold(n->node_type, n->tier);
+}
+
 el_val_t engram_search_json(el_val_t query, el_val_t limit) {
     EngramStore* g = engram_get();
     const char* q = EL_CSTR(query);
@@ -9524,23 +9662,90 @@ el_val_t engram_search_json(el_val_t query, el_val_t limit) {
                 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) {
-                        double sv = eg_sem_term(n, qv, qdim);
-                        if (sv > 0.0) { sem[nsem].idx = i; sem[nsem].sem = sv; nsem++; }
+                    if (sem && n->emb && n->emb_dim == qdim) {
+                        double c = eg_cosine(n->emb, qv, qdim);
+                        /* Semantic leg: identical to eg_sem_term(), which is
+                         * left in place and still used by engram_search().
+                         * Inlined here only so one cosine serves both uses. */
+                        if (c > ENGRAM_EMBED_SEED_MIN) {
+                            double sv = (c - ENGRAM_EMBED_SEED_MIN) / (1.0 - ENGRAM_EMBED_SEED_MIN);
+                            if (sv > 1.0) sv = 1.0;
+                            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);
+                /* 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);
                 /* Claim-10 associative leg: expand the top lexical hits along
                  * structural relations only, order the reached set by query
@@ -9549,12 +9754,82 @@ el_val_t engram_search_json(el_val_t query, el_val_t limit) {
                  * 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, qv, qdim, assoc, ENGRAM_ASSOC_MAX)
+                    ? engram_assoc_leg(g, hits, nhits, semseed, nsemseed,
+                                       qv, qdim, assoc, ENGRAM_ASSOC_MAX)
                     : 0;
                 int64_t* order = malloc((size_t)lim * sizeof(int64_t));
                 if (order) {
-                    int64_t no = engram_interleave3(hits, nhits, sem, nsem,
-                                                    assoc, nassoc, lim, order);
+                    /* ── Layer 1 → background activation, per leg ──
+                     * Each leg's raw score is put on a common [0,1] footing
+                     * WITHOUT blending the legs against each other (that
+                     * failed in the score-fusion cut of the semantic leg —
+                     * two rankings with different spreads cannot be summed).
+                     * Lexical: BM25 over the score a node would earn covering
+                     * every query token at mean field length, so the scale is
+                     * "how much of this query's rare vocabulary did you
+                     * actually account for". Semantic: the shift-and-floor
+                     * value, already in [0,1]. Associative: cosine to the
+                     * query, which is what orders that leg. */
+                    double idf_sum = 0.0;
+                    for (int t = 0; t < ntok; t++) idf_sum += idf[t];
+                    double w_ideal = idf_sum * (ENGRAM_BM25_K1 + 1.0)
+                                   / (1.0 + ENGRAM_BM25_K1);
+                    if (w_ideal <= 0.0) w_ideal = 1.0;
+
+                    int64_t nLs = nhits  < ENGRAM_WM_LEG_SCAN ? nhits  : ENGRAM_WM_LEG_SCAN;
+                    int64_t nSs = nsem   < ENGRAM_WM_LEG_SCAN ? nsem   : ENGRAM_WM_LEG_SCAN;
+                    int64_t nAs = nassoc < ENGRAM_WM_LEG_SCAN ? nassoc : ENGRAM_WM_LEG_SCAN;
+
+                    EngramRankEntry Lp[ENGRAM_WM_LEG_SCAN], Lq[ENGRAM_WM_LEG_SCAN];
+                    EngramSemEntry  Sp[ENGRAM_WM_LEG_SCAN], Sq[ENGRAM_WM_LEG_SCAN];
+                    EngramSemEntry  Ap[ENGRAM_WM_LEG_SCAN], Aq[ENGRAM_WM_LEG_SCAN];
+                    int64_t nLp = 0, nLq = 0, nSp = 0, nSq = 0, nAp = 0, nAq = 0;
+
+                    /* ── Layer 2 → promote or suppress. Nothing is dropped. */
+                    for (int64_t i = 0; i < nLs; i++) {
+                        double bg = hits[i].w / w_ideal;
+                        if (bg > 1.0) bg = 1.0;
+                        if (eg_wm_promote(&g->nodes[hits[i].idx], q, bg, NULL))
+                            Lp[nLp++] = hits[i];
+                        else
+                            Lq[nLq++] = hits[i];
+                    }
+                    for (int64_t i = 0; i < nSs; i++) {
+                        /* RAW cosine, not the shift-and-floor value. The
+                         * first cut of this filter fed pass 2 the shifted
+                         * value, which for a genuine match (c .60-.70) is
+                         * 0.02-0.25 — under every per-type threshold — so the
+                         * whole semantic leg was suppressed while lexical
+                         * junk cleared its gate. Pass 2's thresholds are
+                         * calibrated against activation strengths in [0,1],
+                         * which is the scale raw cosine is on. Measured cost
+                         * of getting this wrong: paraphrase 61.5% -> 23.1%. */
+                        double bg = sem[i].sem * (1.0 - ENGRAM_EMBED_SEED_MIN)
+                                  + ENGRAM_EMBED_SEED_MIN;
+                        if (eg_wm_promote(&g->nodes[sem[i].idx], q, bg, NULL))
+                            Sp[nSp++] = sem[i];
+                        else
+                            Sq[nSq++] = sem[i];
+                    }
+                    for (int64_t i = 0; i < nAs; i++) {
+                        if (eg_wm_promote(&g->nodes[assoc[i].idx], q, assoc[i].sem, NULL))
+                            Ap[nAp++] = assoc[i];
+                        else
+                            Aq[nAq++] = assoc[i];
+                    }
+
+                    /* Promoted material fills the head, in leg order; the
+                     * background-only field follows behind it (claim 45). */
+                    int64_t no = engram_interleave3(Lp, nLp, Sp, nSp,
+                                                    Ap, nAp, lim, order, 0);
+                    if (no < lim)
+                        no = engram_interleave3(Lq, nLq, Sq, nSq,
+                                                Aq, nAq, lim, order, no);
+                    /* Anything past the scanned head of each leg, only if the
+                     * filter left the result short of the caller's limit. */
+                    if (no < lim)
+                        no = engram_interleave3(hits, nhits, sem, nsem,
+                                                assoc, nassoc, lim, order, no);
                     for (int64_t k = 0; k < no; k++) {
                         if (!first) jb_putc(&b, ',');
                         engram_emit_node_json(&b, &g->nodes[order[k]], 0);