{
  "schema_version": "1.0.0",
  "exported_at": "2026-03-05T22:01:19.712135+00:00",
  "data": [
    {
      "model": "gat",
      "scenario": "val",
      "metric_name": "accuracy",
      "value": 0.9986240786240786
    },
    {
      "model": "gat",
      "scenario": "val",
      "metric_name": "precision",
      "value": 0.9923577696009057
    },
    {
      "model": "gat",
      "scenario": "val",
      "metric_name": "recall",
      "value": 0.9917963224893918
    },
    {
      "model": "gat",
      "scenario": "val",
      "metric_name": "f1",
      "value": 0.9920769666100736
    },
    {
      "model": "gat",
      "scenario": "val",
      "metric_name": "specificity",
      "value": 0.999273510022871
    },
    {
      "model": "gat",
      "scenario": "val",
      "metric_name": "balanced_accuracy",
      "value": 0.9955349162561313
    },
    {
      "model": "gat",
      "scenario": "val",
      "metric_name": "mcc",
      "value": 0.9913236375276574
    },
    {
      "model": "gat",
      "scenario": "val",
      "metric_name": "fpr",
      "value": 0.0007264899771290193
    },
    {
      "model": "gat",
      "scenario": "val",
      "metric_name": "fnr",
      "value": 0.008203677510608205
    },
    {
      "model": "gat",
      "scenario": "val",
      "metric_name": "n_samples",
      "value": 40700
    },
    {
      "model": "gat",
      "scenario": "val",
      "metric_name": "auc",
      "value": 0.9995591051869116
    },
    {
      "model": "gat",
      "scenario": "val",
      "metric_name": "kappa",
      "value": 0.9913235899339482
    },
    {
      "model": "gat",
      "scenario": "val",
      "metric_name": "tpr",
      "value": 0.9917963224893918
    },
    {
      "model": "gat",
      "scenario": "val",
      "metric_name": "tnr",
      "value": 0.999273510022871
    },
    {
      "model": "gat",
      "scenario": "val",
      "metric_name": "detection_rate",
      "value": 0.9917963224893918
    },
    {
      "model": "gat",
      "scenario": "val",
      "metric_name": "miss_rate",
      "value": 0.008203677510608205
    },
    {
      "model": "gat",
      "scenario": "val",
      "metric_name": "pr_auc",
      "value": 0.9987656733141211
    },
    {
      "model": "vgae",
      "scenario": "val",
      "metric_name": "accuracy",
      "value": 0.8383783783783784
    },
    {
      "model": "vgae",
      "scenario": "val",
      "metric_name": "precision",
      "value": 0.2958540185160338
    },
    {
      "model": "vgae",
      "scenario": "val",
      "metric_name": "recall",
      "value": 0.6237623762376238
    },
    {
      "model": "vgae",
      "scenario": "val",
      "metric_name": "f1",
      "value": 0.4013469239170004
    },
    {
      "model": "vgae",
      "scenario": "val",
      "metric_name": "specificity",
      "value": 0.8587918740750706
    },
    {
      "model": "vgae",
      "scenario": "val",
      "metric_name": "balanced_accuracy",
      "value": 0.7412771251563472
    },
    {
      "model": "vgae",
      "scenario": "val",
      "metric_name": "mcc",
      "value": 0.3513711746688599
    },
    {
      "model": "vgae",
      "scenario": "val",
      "metric_name": "fpr",
      "value": 0.14120812592492937
    },
    {
      "model": "vgae",
      "scenario": "val",
      "metric_name": "fnr",
      "value": 0.37623762376237624
    },
    {
      "model": "vgae",
      "scenario": "val",
      "metric_name": "n_samples",
      "value": 40700
    },
    {
      "model": "vgae",
      "scenario": "val",
      "metric_name": "auc",
      "value": 0.8124451131665413
    },
    {
      "model": "vgae",
      "scenario": "val",
      "metric_name": "optimal_threshold",
      "value": 0.039579205214977264
    },
    {
      "model": "vgae",
      "scenario": "val",
      "metric_name": "youden_j",
      "value": 0.4828371357440947
    },
    {
      "model": "vgae",
      "scenario": "val",
      "metric_name": "kappa",
      "value": 0.3213896551315959
    },
    {
      "model": "vgae",
      "scenario": "val",
      "metric_name": "tpr",
      "value": 0.6237623762376238
    },
    {
      "model": "vgae",
      "scenario": "val",
      "metric_name": "tnr",
      "value": 0.8587918740750706
    },
    {
      "model": "vgae",
      "scenario": "val",
      "metric_name": "detection_rate",
      "value": 0.6237623762376238
    },
    {
      "model": "vgae",
      "scenario": "val",
      "metric_name": "miss_rate",
      "value": 0.37623762376237624
    },
    {
      "model": "vgae",
      "scenario": "val",
      "metric_name": "pr_auc",
      "value": 0.5702150639215626
    },
    {
      "model": "fusion",
      "scenario": "val",
      "metric_name": "accuracy",
      "value": 0.9989
    },
    {
      "model": "fusion",
      "scenario": "val",
      "metric_name": "precision",
      "value": 0.9980252764612955
    },
    {
      "model": "fusion",
      "scenario": "val",
      "metric_name": "recall",
      "value": 0.989041095890411
    },
    {
      "model": "fusion",
      "scenario": "val",
      "metric_name": "f1",
      "value": 0.9935128759583252
    },
    {
      "model": "fusion",
      "scenario": "val",
      "metric_name": "specificity",
      "value": 0.999817817453088
    },
    {
      "model": "fusion",
      "scenario": "val",
      "metric_name": "balanced_accuracy",
      "value": 0.9944294566717495
    },
    {
      "model": "fusion",
      "scenario": "val",
      "metric_name": "mcc",
      "value": 0.9929240551251384
    },
    {
      "model": "fusion",
      "scenario": "val",
      "metric_name": "fpr",
      "value": 0.00018218254691200583
    },
    {
      "model": "fusion",
      "scenario": "val",
      "metric_name": "fnr",
      "value": 0.010958904109589041
    },
    {
      "model": "fusion",
      "scenario": "val",
      "metric_name": "n_samples",
      "value": 30000
    },
    {
      "model": "fusion",
      "scenario": "val",
      "metric_name": "auc",
      "value": 0.9942345890856611
    },
    {
      "model": "fusion",
      "scenario": "val",
      "metric_name": "kappa",
      "value": 0.9929119387866442
    },
    {
      "model": "fusion",
      "scenario": "val",
      "metric_name": "tpr",
      "value": 0.989041095890411
    },
    {
      "model": "fusion",
      "scenario": "val",
      "metric_name": "tnr",
      "value": 0.999817817453088
    },
    {
      "model": "fusion",
      "scenario": "val",
      "metric_name": "detection_rate",
      "value": 0.989041095890411
    },
    {
      "model": "fusion",
      "scenario": "val",
      "metric_name": "miss_rate",
      "value": 0.010958904109589041
    },
    {
      "model": "fusion",
      "scenario": "val",
      "metric_name": "pr_auc",
      "value": 0.9913599265289825
    }
  ]
}