{
  "created_utc": "2026-10-13T13:19:41.718982+00:00",
  "config": "config/probability_calibration/sep_ondj_phase2.json",
  "config_contents": {
    "description": "Phase 2, Pathway A: one-vs-rest binary calibrators (Platt, beta, isotonic) against the incumbent climatology blend; amount correction fixed (docs/48).",
    "benchmark_config": "config/bias_correction/sep_ondj.json",
    "amount_method": "mvs",
    "methods": [
      "climatology_blend",
      "platt_ovr",
      "beta_ovr",
      "isotonic_ovr"
    ],
    "parameters": {
      "platt_ovr": {
        "l2": 0.0001
      }
    },
    "selection": true,
    "selection_region": "ethiopia",
    "output_root": "outputs/probability_calibration/sep_ondj/phase2_binary",
    "selection_folds": 6
  },
  "protocol": "Phase 1 probability-calibration benchmark (docs/48): which tercile-probability method gives the best published probabilities?\n\nPathway A: the amount correction is fixed (the operational MVS, configurable); the probability-calibration stage is replaced.\nFor each target, nested year-based validation over the training years:\n  outer leave-one-year-out: for the left-out year y every fit uses only the other training years \u2014 the amount correction and\n  terciles (each inner year z from a fit without y and z), and every calibrator's parameters, fitted on the inner out-of-fold\n  records of the other years; the calibrated probabilities of year y are then scored.\n  test years: fits on all training years (calibrators on their leave-one-year-out records), scored on the test years\n  (exploratory).\n  SEL: a calibrator is chosen for each outer year by inner cross-validation of the calibrators (blocks of consecutive\n  years, 'selection_folds') on the inner records only (lowest inner RPS), so its score includes the choice among the methods.\nScores (per year, area-weighted over a region; equal years): RPS/RPSS (primary), category Brier scores and skill, log loss\nand its skill against climatology, reliability tables. Tests: each method against the incumbent climatology blend, paired\nwhole-year sign-flip, Holm across every method and target; SEL against the incumbent, Holm across the targets; no harm over\nthe test years.\n\n  python scripts/prob_benchmark.py --config config/probability_calibration/sep_ondj.json",
  "provenance": {
    "commit": "6d8236d4a4451887bffc84aaee53f54723a9d820",
    "uncommitted_changes": false,
    "uncommitted_check": "code and configuration files this result depends on",
    "code_sha256": {
      "scripts/bias_methods.py": "f964fac9e23a92ba01fc39368d996aa660561cd8708f7552fbedc0627f6b3706",
      "scripts/bias_benchmark.py": "bd5d0cce44fa15275cc64fbaa1d9317aaefb43626b0f3a0b9c6a719c3b4fa24f",
      "scripts/bias_confirmation.py": "bbc95e4cb64256b101b5c0b30e2f351c5cd2b36893d4dfb0505c63577243f558",
      "scripts/significance.py": "3143761d5d201e4e62df9ad923757b952a3ea768b060c8a722afcd9b3d6a9963",
      "scripts/calibration_core.py": "f0635cc563e6d6aedb62799847b83fbb0f5cc12ee9f8c48ad48dda15a054fb62",
      "scripts/compare_calibration.py": "9aa137c9a02672ffacc2541cfd23cdab9b3294bf7cc77580a11e21208560866a",
      "scripts/local_blend.py": "ada5c571fb7762d2c333f83ad119d35f0784b82aa2cc35449a44cdf00c53c17d",
      "scripts/run_calibration.py": "1f34e8fc92fdd15983f1633de67fcb6a35882911b6b7072ca865df99d907afd0",
      "scripts/run_monthly.py": "dc13dfb54b78773afb6d0c25ebac8769552e5c071f5d2aed9ba2a01400e44f79",
      "scripts/cycle.py": "00e076fc93dc2c8a5caebf6a209fc3de09a5f69e16c2e7cb20bd7b36d2ecdcba",
      "scripts/common.py": "72b83f5c530017e317ea43af3a0e430e6d03f361bc032de374a0f942435cb0a1"
    },
    "config": {
      "path": "config/bias_correction/sep_ondj.json",
      "sha256": "3c5c2ef194f529714cacf8e4e8c6332254fd8b536a48f6dbf5613d582d9651bc"
    },
    "project_config": {
      "path": "config/ondj/project.json",
      "sha256": "e9ad8cfb30b21a731e86222ae0b592df124600d457d6fcd46d7a508a831c63de"
    },
    "cycle_config": {
      "path": "config/cycles/sep_2026_ondj.json",
      "sha256": "3f33a9615060aaefd7d2bd7318817a4d1b98ef57fc57132e6a48690a518349ab"
    },
    "masks": {
      "cells": {
        "path": "data/masks/ethiopia_common.nc",
        "sha256": "57ad8861c598abb9f175012920e5d0ef058e5b643cd6e4987cad3da6ac0b9e16"
      },
      "ethiopia": {
        "path": "data/masks/ethiopia_common.nc",
        "sha256": "57ad8861c598abb9f175012920e5d0ef058e5b643cd6e4987cad3da6ac0b9e16"
      },
      "ondj_domain": {
        "path": "data/masks/init09_ONDJ_regime_domain.nc",
        "sha256": "336c572d69af3c718de2ef0e537a2d2d98d73b98cab9b02f0b234501a523d83f"
      }
    },
    "inputs": {
      "Oct": {
        "folder": "data/processed/init09_Oct",
        "files": 65,
        "sha256": "0d2561be8800f597bd5f38f02dc670c9861a3aea08dc795d0d3e1105a909b6db"
      },
      "Nov": {
        "folder": "data/processed/init09_Nov",
        "files": 65,
        "sha256": "73d9d400dfa5457a448855f4a211901bf6884d03575b6efeee391376f3fa995a"
      },
      "Dec": {
        "folder": "data/processed/init09_Dec",
        "files": 65,
        "sha256": "df5a657046e479f4a70116e69305bec1938217a49df5b88475b272b397354a2d"
      },
      "Jan": {
        "folder": "data/processed/init09_Jan",
        "files": 65,
        "sha256": "fc51a4c4480bdc0b21d3f968861435ae0221b9660a0cd98c3ced69adad04e489"
      },
      "ONDJ": {
        "folder": "data/processed/init09_ONDJ",
        "files": 65,
        "sha256": "a8ba572412dc96aef88757296d4a01c83453576b53f79bf2ec734bd88c073fa7"
      }
    },
    "scoring_version": 3,
    "dependency_sha256": "4eb76abd6932ecd5356c72c3ee968a7b500ae82cdb667b598757197a49690a9f",
    "python": "3.11.9",
    "numpy": "1.26.4"
  },
  "phase": 1,
  "pathway": "A: fixed amount correction, replaced probability calibration",
  "amount_method": "mvs",
  "incumbent": "climatology_blend",
  "methods": [
    "climatology_blend",
    "platt_ovr",
    "beta_ovr",
    "isotonic_ovr"
  ],
  "version": 1,
  "registry": {
    "climatology_blend": {
      "name": "Climatology blend (incumbent)",
      "inputs": "smoothed probabilities and training climatology",
      "multiclass": "joint",
      "parameters": "lambda: one per target, minimum RPS",
      "references": [
        "Rajagopalan et al. 2002"
      ],
      "incumbent": true,
      "outputs": "tercile probabilities only (no CDF)"
    },
    "platt_ovr": {
      "name": "Platt (sigmoid) calibration, one-vs-rest + normalization",
      "inputs": "logit of each smoothed category probability",
      "multiclass": "one-vs-rest, then divided by the sum",
      "parameters": "2 per category (intercept, slope), L2 1e-4 on the slope, binary log loss",
      "references": [
        "Platt 1999"
      ],
      "incumbent": false,
      "outputs": "tercile probabilities only (no CDF)"
    },
    "beta_ovr": {
      "name": "Beta calibration, one-vs-rest + normalization",
      "inputs": "ln p_k and ln(1 - p_k) of each smoothed category probability",
      "multiclass": "one-vs-rest, then divided by the sum",
      "parameters": "3 per category (c, a >= 0, b >= 0), binary log loss",
      "references": [
        "Kull et al. 2017"
      ],
      "incumbent": false,
      "outputs": "tercile probabilities only (no CDF)"
    },
    "isotonic_ovr": {
      "name": "Isotonic regression, one-vs-rest + normalization",
      "inputs": "each smoothed category probability",
      "multiclass": "one-vs-rest, then divided by the sum",
      "parameters": "monotone step map per category, pooled over cells and years (weighted pool-adjacent-violators)",
      "references": [
        "Zadrozny & Elkan 2002"
      ],
      "incumbent": false,
      "outputs": "tercile probabilities only (no CDF)"
    }
  },
  "regions": {
    "ethiopia": "All Ethiopia",
    "ondj_domain": "ONDJ R3 (Deyr) domain"
  },
  "primary_region": "ethiopia",
  "training_years": [
    1993,
    2016
  ],
  "test_years": [
    2017,
    2024
  ],
  "targets": {
    "Oct": {
      "tag": "init09_Oct",
      "methods": {
        "climatology_blend": {
          "training": {
            "ethiopia": {
              "years": [
                1993,
                1994,
                1995,
                1996,
                1997,
                1998,
                1999,
                2000,
                2001,
                2002,
                2003,
                2004,
                2005,
                2006,
                2007,
                2008,
                2009,
                2010,
                2011,
                2012,
                2013,
                2014,
                2015,
                2016
              ],
              "per_year": {
                "rps": [
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                  0.4180269314854892,
                  0.4520181291545821,
                  0.47847269882827337,
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              "rps": 0.44766162936482345,
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              "bss_below": 0.012893225527570662,
              "bss_above": 0.012619757692870825,
              "log_loss": 1.0803463817852534,
              "log_loss_skill": 0.014999700287921414,
              "reliability": {
                "below": {
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                }
              }
            },
            "ondj_domain": {
              "years": [
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                1995,
                1996,
                1997,
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                1999,
                2000,
                2001,
                2002,
                2003,
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                2009,
                2010,
                2011,
                2012,
                2013,
                2014,
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              ],
              "per_year": {
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