2 commits

Author	SHA1	Message	Date
Giorgio Gilestro	a40ace1821	second review round: tempered claims, robust statistics, corrected technical statements ... Analyses (figures/stats_llm_epistasis.py, committed + reproducible): condition-clustered bootstrap CIs (functional measures exclude zero: dis_raw [+0.04,+0.69], conf-weighted [+0.02,+0.68]; gradient alignment [-0.59,-0.06]; geometry straddles zero), PAIRED predictor contrasts (not individually significant — stated), leave-one-condition-out held-out prediction (functional replicates, geometry ~0, performance baseline unstable), three outcome references (ordering sensitive to reference — reported, with the mechanism), between/within-axis decomposition (within-conflict identification impossible by design; the compat axis identifies), and seed-level paired reliability (routing/directed beat soup 3/3 seeds incl. one catastrophic soup failure; CI-width fragility claim withdrawn). Renames and corrections: "decisive experiment" -> "controlled predictive test"; "operational epistasis" -> "confidence-weighted functional conflict (proposed proxy)"; "functional by construction" -> "controls a major source of coordinate mismatch / conflict-associated" (module, configs, READMEs, figures); SI proposition's "chord" defined precisely (endpoint-loss interpolation, invariant) vs the path (not invariant) + no-global-optimality caveat (removable = lower bound, residual = upper); snowball count != performance cliff distinction added; claims table gains four rows (grid finding / weighting NOT supported / functional-vs- all-geometry not established / operator choice open); §1 ladder states the prediction rung as a bounded small-model result. paper/response-to-review-2.md: point-by-point, opening with the bookkeeping correction (E13b/c were in the reviewed draft — revised interpretation, not new results). READMEs rewritten around the four analyses with the chronology (prospective/adaptive/post-hoc) disclosed. 151 tests green. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01BkRLcc18rwT2Lysu6PbG7v	2026-09-06 17:55:46 +01:00
Giorgio Gilestro	287d2326cc	epistasis_predicts: functional conflict, not weight geometry, predicts merge failure pre-merge ... The decisive experiment from the external review. 39 LoRA parent pairs (0.5B, 3 seeds) on three axes decorrelated by construction: conflict (contradictory conventions on shared prompts, private budgets fixed), compat (same prompts, SAME convention — overlap without conflict), and duration (weight divergence, zero conflict). Six pre-merge predictors; primary outcome = merge penalty (parent potential − merged achieved). League table (Spearman vs penalty, n=39): functional measures predict (dis_raw +0.460, epi_conf +0.446, p<0.005); geometry collapses (delta_cos +0.03, delta_l2 +0.17 n.s.); gradient alignment weak (−0.35); performance ~0. The first grid's apparent geometry win (+0.60) was an overlap/volume artifact — the compat control axis (added for exactly this) exposed and killed it: same overlap and data volume, zero penalty. Honest riders in the README: confidence weighting does not beat raw disagreement as a rank predictor (pre-registered internal prediction not confirmed; it does double the conflict/compat level contrast), and |rho|~0.45 is bounded by 0.5B merge-outcome noise (7B is the firm-up). Also: micro-batched gradient accumulation (OOM fix on the shared 16GB GPU), exact r-space LoRA-delta geometry (brute-force-verified test, 151 green), systemd-run runbook lesson (tmux dies with the SSH session scope on this box). Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01BkRLcc18rwT2Lysu6PbG7v	2026-09-06 17:19:46 +01:00