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First good B1 results

2026-09-17. A full-budget seed42 comparison used the existing dataset, all three season folds, forecast-loss epoch selection followed by refitting, and 2,048 predictive trajectories. A reused a verified completed run; B and C ran on GPUs.

Forecast performance

Scores use the shared frozen-support scorer: location-relative WIS against the Hub ensemble, with the established geography/target weights and equal seasons. The ensemble benchmark is 1.0; lower is better.

Candidate Natural score Improvement over ensemble Improvement over A
A: rank-1 direct, masking 0.5 0.989394 1.06%
B: A + supplied-final flags 0.941934 5.81% 4.80%
C: B + parallel nowcast head 0.958547 4.15% 3.12%

C uses forecast loss + 0.25 × nowcast loss, without feeding nowcast predictions into forecasting. B beats the ensemble on all six target scores averaged across seasons. Relative to A, it improves five targets; influenza admissions worsen by about 2.05%.

Input condition A B C
Natural 0.989394 0.941934 0.958547
Recent masking 1.121713 1.078939 1.080418
Gap 0.989807 0.942306 0.958680
Outage 1.343990 1.316628 1.296242

Stress scores retain the same frozen tasks and ensemble benchmark; only the model's inputs are stressed. B improves every stress point score relative to A.

How much of the input is vintage data?

On the actual ensemble-scored support, deduplicating horizons and counting each target/location/issuance once, 13,920 of 14,497 combinations (96.0%) have vintage reports for both recent weeks. 657 of 28,994 recent input cells (2.3%) use the supplied-final fallback. These are unweighted input counts, not shares of the weighted score.

The audit joins forecast-cells-natural.parquet from B's seed42 attempt002 to build_b1_wednesday_calendar.npz: issuance is Hub reference date minus three days, locations map from FIPS to postal codes, and the two most recent cells are classified using X_available and X_final.

Thus the comparison mostly uses vintage recent inputs. Older history is finalized throughout, and missing recent reports can receive later finals. Scoring uses the same finalized observations for the model and ensemble. This is retrospective conditional forecasting, not a strict real-time backtest. Hub forecast availability does not guarantee complete vintage input coverage.

Calibration and uncertainty

Under the score's geography/target weighting and equal-season averaging:

Candidate 50% interval coverage 95% interval coverage
A 45.37% 87.63%
B 43.97% 86.75%
C 41.61% 85.80%

All three under-cover. B's lower WIS does not imply better calibration.

The primary paired 8-week temporal interval for B/A relative WIS change is [-10.52%, +0.09%]; C/A is [-6.49%, +3.72%]. Both include zero. These intervals condition on seed42's fitted models and on retaining scoring support: 827 of 2,000 block draws were excluded for missing positive-denominator support. Four-/12-week sensitivity intervals favor B over A but do not replace the preselected primary interval. There is no across-seed uncertainty estimate or ten-fit predictive mixture yet, and these intervals do not test superiority over the ensemble.

Recommendation: continue iterating on B. It has the best natural score and is simpler than C. Retain A under the formal promotion rule: B's 4.80% gain falls short of the fixed 5% threshold, the primary interval includes zero, and the ten-seed experiment remains deferred.

Execution and next settings

B job1491695 completed in 25:17; C job1491696 in 34:37; report job1491906 in 1:00. Completion notifications were enabled. B spent roughly half its time fitting/selecting and half evaluating; final shared scoring took about 16 seconds. The long daytime runs were cancelled and were not restarted overnight.

New code defaults to 256 evaluation trajectories, with training and validation budgets unchanged. This trades evaluation precision for faster iteration. The results above and the old pinned plans remain at 2,048; use new 256-draw plans and reevaluate reused checkpoints consistently before combining results. Mixed evaluation budgets are rejected by the decisive report.

Artifacts: data/experiments/B1-seed42-report/ contains the score tables, paired differences, calibration, temporal sensitivity, recent-head diagnostics, and seed-stress.png. Exact original plan/launch/status/rank commands and job IDs are recorded in the execution note.