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          "month": "2025-01",
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          "month": "2025-04",
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        {
          "month": "2026-01",
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        {
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      ],
      "pooled_ece": 0.0192,
      "pooled_reliability": [
        {
          "bin_lo": 0.0,
          "bin_hi": 0.1,
          "pred_mean": null,
          "emp_freq": null,
          "n": 0
        },
        {
          "bin_lo": 0.1,
          "bin_hi": 0.2,
          "pred_mean": null,
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          "n": 0
        },
        {
          "bin_lo": 0.2,
          "bin_hi": 0.3,
          "pred_mean": 0.2893,
          "emp_freq": 1.0,
          "n": 1
        },
        {
          "bin_lo": 0.3,
          "bin_hi": 0.4,
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          "n": 746
        },
        {
          "bin_lo": 0.4,
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          "n": 15420
        },
        {
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        },
        {
          "bin_lo": 0.6,
          "bin_hi": 0.7,
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          "emp_freq": null,
          "n": 0
        },
        {
          "bin_lo": 0.7,
          "bin_hi": 0.8,
          "pred_mean": null,
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          "n": 0
        },
        {
          "bin_lo": 0.8,
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        },
        {
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          "n": 0
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      ]
    }
  },
  "status": "ok",
  "methodology": "Walk-forward calibration reliability (display-only, leakage-safe). For each realized OOS month T, the Platt calibration map is refit on all realized (score, forward-return) pairs STRICTLY before T, then T's tickers are predicted; T's own realized outcome scores the prediction (backward audit). Per-month OOS ECE shows whether the calibrated P(up) stays trustworthy as the realized sample grows; the pooled reliability diagram bins all walk-forward OOS predictions (mean predicted P vs empirical up-frequency). Only the 2-param display map is refit \u2014 the frozen LightGBM learner is NEVER touched, and no ledger / frozen surface / research estimator is affected. NOT a research claim and NOT a path to positive rank-IC (research verdict ledger #49: combined rank-IC \u22120.0088, NULL)."
}