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            "mean_spearman": 0.04970588235294119,
            "ci95": [
              -0.1307463235294118,
              0.2167683823529411
            ],
            "n_eligible_datasets": 20,
            "n_informative_datasets": 20,
            "informative_dataset_seeds": [
              1000,
              1001,
              1002,
              1003,
              1004,
              1005,
              1006,
              1007,
              1008,
              1009,
              1010,
              1011,
              1012,
              1013,
              1014,
              1015,
              1016,
              1017,
              1018,
              1019
            ],
            "n_constant_proxy_datasets": 0,
            "n_constant_target_datasets": 0,
            "n_undefined_measure_datasets": 0,
            "n_too_few_models_datasets": 0
          }
        },
        "excluded_empty_dataset_seeds": []
      },
      "pooled_descriptive": {
        "Leb_wrong": {
          "n_models": 320,
          "pearson": 0.9999999999999999,
          "spearman": 1.0
        },
        "label_changes": {
          "n_models": 320,
          "pearson": 0.48246425188419195,
          "spearman": 0.4617724525138099
        },
        "wrong_label_count": {
          "n_models": 320,
          "pearson": 0.7119527372506803,
          "spearman": 0.7178220373381922
        },
        "nn_Leb_wrong": {
          "n_models": 320,
          "pearson": 0.9478297335651131,
          "spearman": 0.9383325225004142
        },
        "nb_flips": {
          "n_models": 320,
          "pearson": 0.4863623315760469,
          "spearman": 0.4977409539396755
        },
        "nb_regions": {
          "n_models": 320,
          "pearson": -0.008924514277794813,
          "spearman": -0.012926245949186205
        },
        "Lmax": {
          "n_models": 320,
          "pearson": -0.04444317865646095,
          "spearman": -0.07372300999033195
        },
        "Lavg": {
          "n_models": 320,
          "pearson": -0.3786487562297641,
          "spearman": -0.2325048340315823
        },
        "Lavg_flip": {
          "n_models": 320,
          "pearson": -0.09234903809598406,
          "spearman": -0.01086045762165646
        },
        "band_mass_0.1": {
          "n_models": 320,
          "pearson": 0.11132516476314491,
          "spearman": 0.22249985351419452
        },
        "band_mass_0.2": {
          "n_models": 320,
          "pearson": 0.13327162338186804,
          "spearman": 0.22483556968329768
        },
        "band_mass_0.5": {
          "n_models": 320,
          "pearson": 0.14145984953326893,
          "spearman": 0.22898661119737496
        },
        "band_mass_1.0": {
          "n_models": 320,
          "pearson": 0.19769498247291922,
          "spearman": 0.23973354231974925
        },
        "flat_rel": {
          "n_models": 320,
          "pearson": 0.2602826662269818,
          "spearman": 0.3400067383470542
        },
        "sam_sharp": {
          "n_models": 320,
          "pearson": 0.17262952532234666,
          "spearman": 0.10252578150177248
        },
        "hess_power": {
          "n_models": 320,
          "pearson": 0.22804122410932426,
          "spearman": 0.37699403802771514
        },
        "normalized_band_mass_0.1": {
          "n_models": 320,
          "pearson": -0.07698427441941812,
          "spearman": -0.16145189406146543
        },
        "normalized_band_mass_0.2": {
          "n_models": 320,
          "pearson": -0.07485303436676949,
          "spearman": -0.12406835027685817
        },
        "normalized_band_mass_0.5": {
          "n_models": 320,
          "pearson": -0.04746487424750173,
          "spearman": -0.09568013359505464
        },
        "normalized_band_mass_1.0": {
          "n_models": 320,
          "pearson": 0.14031544181797864,
          "spearman": 0.06951813494272405
        },
        "normalized_Lmax": {
          "n_models": 320,
          "pearson": 0.24878659420990268,
          "spearman": 0.35868001640641023
        },
        "normalized_Lavg": {
          "n_models": 320,
          "pearson": 0.4348054100494276,
          "spearman": 0.4161134386077989
        },
        "normalized_margin_min": {
          "n_models": 320,
          "pearson": 0.003690147958631405,
          "spearman": 0.1204424603755896
        },
        "normalized_margin_q10": {
          "n_models": 320,
          "pearson": 0.12251937743768426,
          "spearman": 0.21727031025693608
        }
      }
    }
  },
  "notes": [
    "Only completed dataset blocks enter correlations; all attempted fits remain recorded.",
    "Intervals resample datasets with defined correlations; inspect coverage for each proxy.",
    "No multiple-comparison correction; measures and thresholds fixed before the suite.",
    "High pooled correlation can reflect dataset differences. Dataset-only measures cannot rank fits within a dataset.",
    "Wrong-label count, nearest-neighbour disagreement and model disagreement use the known clean rule.",
    "Positive normalized training margins suggest better separation: a useful margin may correlate negatively with error.",
    "Interpolation and training error use float32 counts; float64 count mismatches are reported separately."
  ]
}
