Day 28 of 78 · Run #18 · 2026-09-16
mean-corrected kd_std=4.0 — overall +0.0122 (rank 564); more mean-1 spread helps marginally (s2.0 +0.0090) but stays far under the biased champion (+0.0511). Applied delta magnitude, not dispersion-at-mean-1, is what the score rewards.
Overall score 0.012 · Perturbation discrimination (pds) 0.290 · +5 more
k010 s4.0 scored overall +0.0122 (rank 564): nmae +0.019, pds 0.290, fid -0.292, reach 0.077 — marginal gain over s2.0 (+0.0090) but far below the uncorrected champion (+0.0511). The k009/k010 pair is now conclusive: at mean-1, no eta shape or spread tested recovers what the clipped trunc-normal's ~40% mean inflation delivered. The effective driver is applied delta magnitude — borrowed K562/Atlas signatures appear systematically weak in the 2026 contexts, and the 'bias' was compensating. Next honest lever: explicit delta-scale calibration (or context-conditioned Layer A scaling), not more eta-distribution search.
Scorecard
All six VCC metrics — best-in-series is highlighted.
| Metric | Value | |
|---|---|---|
| Overall score | +0.0122 | |
| Perturbation discrimination (pds) | +0.2899 | |
| Expression accuracy (mse) | +0.0000 | best |
| DE log-FC accuracy (nmae) | +0.0185 | |
| DE direction fidelity (fid) | -0.2920 | |
| DE direction reach (reach) | +0.0774 | |
| Significance overlap (jac) | -0.0208 |
Audit & metrics Overall score 0.012 · Perturbation discrimination (pds) 0.290 · +5 more
No audit flags.
Metrics vs ceiling (all scores)
Differential expression volcano plot (log2FC vs -log10 p)
Pre-registered hypotheses (1)
- If mean-1 spread was the issue, s4.0 (std 1.24) should approach the champion; if applied mean magnitude is the driver it stays well below +0.05
Evidence Literature & entity enrichment
Literature
0 genesTavily · auxiliary, not scored
Literature pending — run tools/enrich_literature.py.
Field context
VCC / perturbation researchField research pending — run tools/enrich_newsroom.py.
Biomedical NER
0 entitiesPioneer GLiNER2 · fine-tuned on Tavily literature when available · regex fallback offline
NER pending — run tools/pioneer_ner.py --train once, then tools/pioneer_ner.py --run experiments/<run-id>.
Narrative digest run digest · traces to facts.json
Narrative pending — run tools/render_narrative.py.
Trust & provenance Self-tests + reproduce command
6 pipeline steps · sourced from committed artifacts only
No metrics CSVs found — run cell-eval and commit results.
Ran 5 deterministic rules · 0 flags raised (none fired).
Literature enrichment not yet run — execute tools/enrich_literature.py.
NER extraction not yet run — execute tools/pioneer_ner.py.
Narrative not yet generated — execute tools/render_narrative.py.
Verification artifacts not yet committed — run planted_signal.py, holo_audit.py, check_narrative.py.