preregistration: week-long canonical-schema study design#153
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Comprehensive 7-day study spec: run each model once on the largest cached FRED universe (both regimes, all frequencies), record per-step PREDICTIONS in the canonical predictions.py schema, derive everything (LL, CRPS, DM win/draw/loss, sandwich lifts, calibration, meta-feature map, allocation-vs-selection). Tiered by cost (fast whole-universe / medium sandwich / slow arms in own envs with timeouts). Pre-registered hypotheses H1-H5 incl. "does blending pay where selecting did not." Resumable, 7-day caffeinate, commit derived summaries. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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7-day study spec — run each model once on the largest cached FRED universe (both regimes), record per-step predictions in the canonical
predictions.pyschema, derive everything (LL/CRPS/DM win-draw-loss/sandwich lifts/calibration/meta-features/allocation). Tiered by cost, resumable, pre-registered H1-H5.🤖 Generated with Claude Code