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🎲SimulationsπŸ§ͺLab≣Catalog?How this works

gap-filter fit for live executor

← lab Β· n train 13,698 Β· base rate model right 0.4915 Β· ran 7/12/2026

What this is: A one-off study β€” its numbers below are exactly what the run reported.
n train13,698
artifact/app/data/downloads/gap_filter.joblib
base rate model right0.4915

Reading the columnswhat each number actually means

AUCpredictability: 0.50 = coin flip, ~0.70 = ceiling for sports
Importancehow much the model leans on this factor (permutation importance)
Directionsign of the raw correlation with the outcome
Survives all eraseffect points the same way in every historical era
Spec Β· the reproducible recipe
{
  "kind": "gap_filter_fit",
  "seed": 42,
  "model_run": 18
}