{
  "schema_version": 1,
  "columns": [
    "baseline",
    "comparison",
    "contrast",
    "scope",
    "estimate",
    "ci_low",
    "ci_high",
    "valid_resamples",
    "interval_status"
  ],
  "rows": [
    {
      "baseline": "Flash-Lite MINIMAL corrected",
      "comparison": "Flash-Lite LOW",
      "contrast": "accuracy_gain_night_ir_minus_day",
      "scope": "exploratory_composition_confounded_no_causal_interaction_claim",
      "estimate": "0.0021954038574537177",
      "ci_low": "-0.04255206944834574",
      "ci_high": "0.04467756816696078",
      "valid_resamples": "10000",
      "interval_status": "ok"
    },
    {
      "baseline": "Flash-Lite MINIMAL corrected",
      "comparison": "Flash-Lite MEDIUM",
      "contrast": "accuracy_gain_night_ir_minus_day",
      "scope": "exploratory_composition_confounded_no_causal_interaction_claim",
      "estimate": "-0.0241558995021599",
      "ci_low": "-0.07526696430321692",
      "ci_high": "0.02626177034707838",
      "valid_resamples": "10000",
      "interval_status": "ok"
    },
    {
      "baseline": "Flash-Lite MINIMAL corrected",
      "comparison": "Flash-Lite HIGH",
      "contrast": "accuracy_gain_night_ir_minus_day",
      "scope": "exploratory_composition_confounded_no_causal_interaction_claim",
      "estimate": "-0.014967488651699182",
      "ci_low": "-0.06545030206406034",
      "ci_high": "0.03526475080646183",
      "valid_resamples": "10000",
      "interval_status": "ok"
    },
    {
      "baseline": "Flash-Lite LOW",
      "comparison": "Flash-Lite MEDIUM",
      "contrast": "accuracy_gain_night_ir_minus_day",
      "scope": "exploratory_composition_confounded_no_causal_interaction_claim",
      "estimate": "-0.026351303359613606",
      "ci_low": "-0.07172268778789254",
      "ci_high": "0.0189690351423684",
      "valid_resamples": "10000",
      "interval_status": "ok"
    },
    {
      "baseline": "Flash-Lite LOW",
      "comparison": "Flash-Lite HIGH",
      "contrast": "accuracy_gain_night_ir_minus_day",
      "scope": "exploratory_composition_confounded_no_causal_interaction_claim",
      "estimate": "-0.0171628925091529",
      "ci_low": "-0.06856400410423294",
      "ci_high": "0.03472805425803245",
      "valid_resamples": "10000",
      "interval_status": "ok"
    },
    {
      "baseline": "Flash-Lite MEDIUM",
      "comparison": "Flash-Lite HIGH",
      "contrast": "accuracy_gain_night_ir_minus_day",
      "scope": "exploratory_composition_confounded_no_causal_interaction_claim",
      "estimate": "0.009188410850460712",
      "ci_low": "-0.0333059140673282",
      "ci_high": "0.05342221517742006",
      "valid_resamples": "10000",
      "interval_status": "ok"
    },
    {
      "baseline": "Gemini 3.8 HIGH media / MEDIUM thinking",
      "comparison": "Gemini 3.8 HIGH media / LOW thinking",
      "contrast": "accuracy_gain_night_ir_minus_day",
      "scope": "exploratory_composition_confounded_no_causal_interaction_claim",
      "estimate": "-0.014864175528995473",
      "ci_low": "-0.053898944091011335",
      "ci_high": "0.02446934204963396",
      "valid_resamples": "10000",
      "interval_status": "ok"
    },
    {
      "baseline": "Gemini 3.8 HIGH media / MEDIUM thinking",
      "comparison": "Gemini 3.8 HIGH media / HIGH thinking",
      "contrast": "accuracy_gain_night_ir_minus_day",
      "scope": "exploratory_composition_confounded_no_causal_interaction_claim",
      "estimate": "0.043339854974204006",
      "ci_low": "-0.003532461928760123",
      "ci_high": "0.08899993042211726",
      "valid_resamples": "10000",
      "interval_status": "ok"
    },
    {
      "baseline": "Gemini 3.8 HIGH media / LOW thinking",
      "comparison": "Gemini 3.8 HIGH media / HIGH thinking",
      "contrast": "accuracy_gain_night_ir_minus_day",
      "scope": "exploratory_composition_confounded_no_causal_interaction_claim",
      "estimate": "0.058204030503199486",
      "ci_low": "0.011150880832116157",
      "ci_high": "0.10484934398416709",
      "valid_resamples": "10000",
      "interval_status": "ok"
    }
  ],
  "unit_policy": {
    "table": "exploratory_time_interactions.csv",
    "metric_units": {},
    "counts": {
      "valid_resamples": "bootstrap_resamples"
    },
    "interval": "ci_low and ci_high use the same units as estimate; pointwise 95% when interval_status is ok",
    "estimate": "signed_proportion_difference; night_IR_accuracy_gain minus day_accuracy_gain",
    "scope": "exploratory composition-confounded contrast, not a causal interaction"
  },
  "note": "Saved aggregate candidate analysis; intervals are pointwise and exploratory tests have separate Holm-adjusted p-values."
}