v0.3: bottleneck task — NDCG@10 + mean-wait baseline + leaderboard#8
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- score_bottleneck — pure-CPython NDCG@k. Predictions rank transitions; truth is the held-out per-(a,b) mean wait time. Missing predictions sink to the bottom (refusing to predict doesn't earn credit) - pm_bench/bottleneck.py — BottleneckTarget + extract; per-transition shape (4-tuple: a, b, mean_wait_seconds, n_observations) instead of per-prefix - baselines/mean_wait.py — train-mean-per-transition with global-mean fallback. On synthetic-toy: NDCG@10 0.9786 over 6 transitions - CLI: --task bottleneck, --baseline mean-wait wired through prefixes / predict / score - leaderboard/bottleneck/synthetic-toy.json with mean-wait-ref entry (NDCG@10 0.9786, n_transitions 6); pm-bench leaderboard --all now walks 3 boards (next-event, remaining-time, bottleneck) - 7 new tests; 86 total, ruff clean - v0.3 marked partial → 4 of 5 tasks (conformance remains)
This was referenced May 1, 2026
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Merged into main as part of the audit-cleanup stack (commit 9c00b47). The full content of this PR is now on main. |
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Stacked on top of #7 (outcome). Merge order: #2 → #3 → #4 → #5 → #6 → #7 → this.
Summary
What's new
score_bottleneck— pure-CPython NDCG@k. Predicted scores rank transitions; truth is the held-out per-(a,b) mean wait time. Missing predictions sink to the bottom (refusing to predict doesn't earn credit).pm_bench/bottleneck.py—BottleneckTarget,BottleneckPrediction,extract_bottleneck_targets, CSV r/w. Per-transition shape (activity_a, activity_b, mean_wait_seconds, n_observations) — different from the per-prefix tasks, intentionally so.pm_bench/baselines/mean_wait.py— train-mean-per-transition with observation-weighted global fallback. ~30 lines.--task bottleneck,--baseline mean-wait. UsageError on mismatched (task, baseline) pairs, consistent with the other tasks.leaderboard.py—_rescore_bottleneckand a new dispatch branch inrescore;standingsnow sorts byndcg_at_kfor bottleneck andaucfor outcome (correctly higher-better for both).pm-bench leaderboardprints task-appropriate columns:mae_daysfor time,aucfor outcome,ndcg@10for bottleneck,top1/top3for next-event.test_bottleneck.py); 86 total, ruff clean.Smoke
Test plan
pytest -q— 86 passed (was 73 on PR v0.3: outcome task — AUC scoring + prior baseline #7)ruff check pm_bench tests— clean--all --verifyworkflowRoadmap impact
[bpi]extra.