Datasets:
Tasks:
Text Classification
Formats:
parquet
Sub-tasks:
semantic-similarity-classification
Languages:
code
Size:
1M - 10M
License:
sync EmbedEd artifacts (phase01-v6)
Browse files- artifacts/gate_runs.json +32 -0
- report/measurements.md +11 -0
- sync_manifest.json +0 -0
artifacts/gate_runs.json
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{
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"runs": [
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{
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"stamp": null,
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"version": "phase01-v6",
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{
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"runs": [
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{
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"stamp": null,
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"version": "phase01-v6",
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"rule": "D1 scale-aware: C1 < C2 <= C3 and d(C1->C2) >= 0.5",
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"ok": true,
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"d_c1_c2": 0.614,
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"ci": [
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0.795,
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1.202
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],
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"recorded_source": null,
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"per_condition": {
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"C1": {
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"mean_cos": 0.96068,
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"std": 0.0257,
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"n_samples": 20000,
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"n_anchors": 1000
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},
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"C2": {
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"mean_cos": 0.97526,
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"std": 0.02162,
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"n_samples": 20000,
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"n_anchors": 1000
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},
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"C3": {
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"mean_cos": 0.98845,
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"std": 0.00722,
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"n_samples": 20000,
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"n_anchors": 1000
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}
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}
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},
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{
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"stamp": null,
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"version": "phase01-v6",
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report/measurements.md
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@@ -488,6 +488,17 @@ Context recorded at the time: ordering C1 < C2 ≤ C3 holds; the C1→C2 gap is
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- legacy absolute-margin rule (0.02): FAIL — C1→C2 gap +0.0146 < margin 0.02 (mining produced equally easy negatives) (reported for the record; not the verdict since v6)
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- **verdict: PASS** — order C1 < C2 <= C3 holds (0.9607 < 0.9753 <= 0.9885) and d(C1→C2) = 0.614 >= 0.5 (absolute gap +0.0146)
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## Gate G1 — diagnostics (scale of the space; no verdict)
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`python -m scripts.hardness_diagnostics` — version `phase01-v6`, 1600 anchors × k=20, corpus 6451. Percentile = share of corpus fragments less similar to the anchor than the negative (50 = random, 100 = nearest).
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- legacy absolute-margin rule (0.02): FAIL — C1→C2 gap +0.0146 < margin 0.02 (mining produced equally easy negatives) (reported for the record; not the verdict since v6)
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- **verdict: PASS** — order C1 < C2 <= C3 holds (0.9607 < 0.9753 <= 0.9885) and d(C1→C2) = 0.614 >= 0.5 (absolute gap +0.0146)
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### run 2026-09-27 16:42 UTC — version `phase01-v6`, rule: D1 scale-aware: C1 < C2 <= C3 and d(C1->C2) >= 0.5
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- C1: mean cos(anchor, negative) = 0.96068 (sd 0.026, n = 20000, anchors = 1000)
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- C2: mean cos(anchor, negative) = 0.97526 (sd 0.022, n = 20000, anchors = 1000)
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- C3: mean cos(anchor, negative) = 0.98845 (sd 0.007, n = 20000, anchors = 1000)
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- corpus percentile of the negative in its anchor's similarity ranking, median: C1 50.1 / C2 91.9 / C3 99.8 (50 = random, 100 = nearest); inside the anchor's top-20: C1 0.3% / C2 15.4% / C3 94.8%
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- embeddings: microsoft/graphcodebert-base max_len=512 n=8063 version=phase01-v5
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- d(C1→C2) = 0.614, 95% CI 0.795–1.202 (2000 resamples over anchors, not negatives)
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- legacy absolute-margin rule (0.02): FAIL — C1→C2 gap +0.0146 < margin 0.02 (mining produced equally easy negatives) (reported for the record; not the verdict since v6)
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- **verdict: PASS** — order C1 < C2 <= C3 holds (0.9607 < 0.9753 <= 0.9885) and d(C1→C2) = 0.614 >= 0.5 (absolute gap +0.0146)
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## Gate G1 — diagnostics (scale of the space; no verdict)
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`python -m scripts.hardness_diagnostics` — version `phase01-v6`, 1600 anchors × k=20, corpus 6451. Percentile = share of corpus fragments less similar to the anchor than the negative (50 = random, 100 = nearest).
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sync_manifest.json
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