{
  "figures": [
    "fig-forest-htru2-curves.png",
    "fig-logistic-htru2-curves.png",
    "fig-held-out-ranking-metrics.png",
    "fig-held-out-calibration.png",
    "fig-held-out-confusion-counts.png",
    "fig-held-out-permutation-importance.png",
    "og-card.png"
  ],
  "generator": {
    "path": "reproduce.py",
    "sha256": "a2ad91d1e3f7cf2a15da4fc10246de57b7adda70c1ab2f229f2e51553a75e510",
    "verify": "uv run --frozen reproduce.py --verify"
  },
  "local_bundle": true,
  "notebook": {
    "path": "forest-in-the-sky.ipynb",
    "sha256": "dbd80db87a923e10360d9a380b1e066debd8387a4303df2e98f1bf3e91114391"
  },
  "numbers": [
    {
      "appears_as": "HTRU2 has 17,898 candidate rows",
      "computation": "Direct audited row count from the parsed HTRU2 source table.",
      "id": "htru2-row-count",
      "receipt": "receipts/analysis.receipt.json",
      "receipt_sha256": "e9a14613cbc18923a803afd3a9b74fc8592c2cdf9643b2179025361e4901cc3c",
      "source": "receipts/analysis.receipt.json#datasets.htru2.dataset.audit.rows",
      "value": 17898
    },
    {
      "appears_as": "HTRU2 includes 1,639 positive-labeled candidates",
      "computation": "Direct count of HTRU2 rows whose parsed class label is positive.",
      "id": "htru2-positive-count",
      "receipt": "receipts/analysis.receipt.json",
      "receipt_sha256": "e9a14613cbc18923a803afd3a9b74fc8592c2cdf9643b2179025361e4901cc3c",
      "source": "receipts/analysis.receipt.json#datasets.htru2.dataset.class_counts.positive",
      "value": 1639
    },
    {
      "appears_as": "Rice has 3,810 grain rows",
      "computation": "Direct audited row count from the parsed Rice source table.",
      "id": "rice-row-count",
      "receipt": "receipts/analysis.receipt.json",
      "receipt_sha256": "e9a14613cbc18923a803afd3a9b74fc8592c2cdf9643b2179025361e4901cc3c",
      "source": "receipts/analysis.receipt.json#datasets.rice.dataset.audit.rows",
      "value": 3810
    },
    {
      "appears_as": "Rice includes 1,630 Cammeo grains",
      "computation": "Direct count of Rice rows whose parsed class label is Cammeo.",
      "id": "rice-positive-count",
      "receipt": "receipts/analysis.receipt.json",
      "receipt_sha256": "e9a14613cbc18923a803afd3a9b74fc8592c2cdf9643b2179025361e4901cc3c",
      "source": "receipts/analysis.receipt.json#datasets.rice.dataset.class_counts.positive",
      "value": 1630
    },
    {
      "appears_as": "HTRU2 dummy prior held-out AP 0.0916",
      "computation": "Direct average_precision value computed on the fixed held-out HTRU2 rows.",
      "id": "htru2-dummy_prior-average_precision",
      "receipt": "receipts/analysis.receipt.json",
      "receipt_sha256": "e9a14613cbc18923a803afd3a9b74fc8592c2cdf9643b2179025361e4901cc3c",
      "source": "receipts/analysis.receipt.json#datasets.htru2.test_metrics.dummy_prior.average_precision",
      "value": 0.09162
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    {
      "appears_as": "HTRU2 dummy prior held-out ROC AUC 0.5000",
      "computation": "Direct roc_auc value computed on the fixed held-out HTRU2 rows.",
      "id": "htru2-dummy_prior-roc_auc",
      "receipt": "receipts/analysis.receipt.json",
      "receipt_sha256": "e9a14613cbc18923a803afd3a9b74fc8592c2cdf9643b2179025361e4901cc3c",
      "source": "receipts/analysis.receipt.json#datasets.htru2.test_metrics.dummy_prior.roc_auc",
      "value": 0.5
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    {
      "appears_as": "HTRU2 logistic regression held-out AP 0.9141",
      "computation": "Direct average_precision value computed on the fixed held-out HTRU2 rows.",
      "id": "htru2-logistic_regression-average_precision",
      "receipt": "receipts/analysis.receipt.json",
      "receipt_sha256": "e9a14613cbc18923a803afd3a9b74fc8592c2cdf9643b2179025361e4901cc3c",
      "source": "receipts/analysis.receipt.json#datasets.htru2.test_metrics.logistic_regression.average_precision",
      "value": 0.91412
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    {
      "appears_as": "HTRU2 logistic regression held-out ROC AUC 0.9756",
      "computation": "Direct roc_auc value computed on the fixed held-out HTRU2 rows.",
      "id": "htru2-logistic_regression-roc_auc",
      "receipt": "receipts/analysis.receipt.json",
      "receipt_sha256": "e9a14613cbc18923a803afd3a9b74fc8592c2cdf9643b2179025361e4901cc3c",
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    {
      "appears_as": "HTRU2 random forest held-out AP 0.9262",
      "computation": "Direct average_precision value computed on the fixed held-out HTRU2 rows.",
      "id": "htru2-random_forest-average_precision",
      "receipt": "receipts/analysis.receipt.json",
      "receipt_sha256": "e9a14613cbc18923a803afd3a9b74fc8592c2cdf9643b2179025361e4901cc3c",
      "source": "receipts/analysis.receipt.json#datasets.htru2.test_metrics.random_forest.average_precision",
      "value": 0.926209
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    {
      "appears_as": "HTRU2 random forest held-out ROC AUC 0.9767",
      "computation": "Direct roc_auc value computed on the fixed held-out HTRU2 rows.",
      "id": "htru2-random_forest-roc_auc",
      "receipt": "receipts/analysis.receipt.json",
      "receipt_sha256": "e9a14613cbc18923a803afd3a9b74fc8592c2cdf9643b2179025361e4901cc3c",
      "source": "receipts/analysis.receipt.json#datasets.htru2.test_metrics.random_forest.roc_auc",
      "value": 0.976684
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    {
      "appears_as": "HTRU2 random-forest-minus-logistic-regression held-out AP +0.0121 [+0.0012, +0.0257]",
      "computation": "Random-forest average precision minus logistic-regression average precision, with the paired class-stratified bootstrap endpoints.",
      "id": "htru2-paired-ap-difference",
      "receipt": "fig-held-out-ranking-metrics.receipt.json",
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      "source": "fig-held-out-ranking-metrics.receipt.json#plotted_data.htru2.average_precision.random_forest_minus_logistic_regression",
      "value": {
        "lower": 0.001192,
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    },
    {
      "appears_as": "Rice dummy prior held-out AP 0.4278",
      "computation": "Direct average_precision value computed on the fixed held-out Rice rows.",
      "id": "rice-dummy_prior-average_precision",
      "receipt": "receipts/analysis.receipt.json",
      "receipt_sha256": "e9a14613cbc18923a803afd3a9b74fc8592c2cdf9643b2179025361e4901cc3c",
      "source": "receipts/analysis.receipt.json#datasets.rice.test_metrics.dummy_prior.average_precision",
      "value": 0.427822
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    {
      "appears_as": "Rice dummy prior held-out ROC AUC 0.5000",
      "computation": "Direct roc_auc value computed on the fixed held-out Rice rows.",
      "id": "rice-dummy_prior-roc_auc",
      "receipt": "receipts/analysis.receipt.json",
      "receipt_sha256": "e9a14613cbc18923a803afd3a9b74fc8592c2cdf9643b2179025361e4901cc3c",
      "source": "receipts/analysis.receipt.json#datasets.rice.test_metrics.dummy_prior.roc_auc",
      "value": 0.5
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    {
      "appears_as": "Rice logistic regression held-out AP 0.9643",
      "computation": "Direct average_precision value computed on the fixed held-out Rice rows.",
      "id": "rice-logistic_regression-average_precision",
      "receipt": "receipts/analysis.receipt.json",
      "receipt_sha256": "e9a14613cbc18923a803afd3a9b74fc8592c2cdf9643b2179025361e4901cc3c",
      "source": "receipts/analysis.receipt.json#datasets.rice.test_metrics.logistic_regression.average_precision",
      "value": 0.964298
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    {
      "appears_as": "Rice logistic regression held-out ROC AUC 0.9688",
      "computation": "Direct roc_auc value computed on the fixed held-out Rice rows.",
      "id": "rice-logistic_regression-roc_auc",
      "receipt": "receipts/analysis.receipt.json",
      "receipt_sha256": "e9a14613cbc18923a803afd3a9b74fc8592c2cdf9643b2179025361e4901cc3c",
      "source": "receipts/analysis.receipt.json#datasets.rice.test_metrics.logistic_regression.roc_auc",
      "value": 0.968833
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    {
      "appears_as": "Rice random forest held-out AP 0.9607",
      "computation": "Direct average_precision value computed on the fixed held-out Rice rows.",
      "id": "rice-random_forest-average_precision",
      "receipt": "receipts/analysis.receipt.json",
      "receipt_sha256": "e9a14613cbc18923a803afd3a9b74fc8592c2cdf9643b2179025361e4901cc3c",
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    {
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      "receipt": "receipts/analysis.receipt.json",
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    "receipts/test-predictions.csv": "97203d66565630a1480818fef8f8e6b439b9358cea5fc955a61c06f9f636f0d3",
    "receipts/training-cv-tuning.csv": "3318a9debe08f495c83a757df5459f9b551e0c75d12a6380db878c8f8e7320ee",
    "reproduce.py.lock": "004d05f217f53bb88abdddb954262afa464daa0366fddb3d35fc11b65e82cfb9",
    "source-manifest.json": "44457cad787a123fbcc8515629d5ac1fc6d9824277355de7e33764121d901a27"
  },
  "reference_environment": {
    "architecture": "arm64",
    "figure_font": "DejaVuSans.ttf",
    "figure_font_sha256": "3fdf69cabf06049ea70a00b5919340e2ce1e6d02b0cc3c4b44fb6801bd1e0d22",
    "freetype_version": "2.6.1",
    "matplotlib_backend": "Agg",
    "matplotlib_version": "3.10.3",
    "numpy_version": "2.3.2",
    "operating_system": "Darwin",
    "os_release": "25.5.0",
    "python_implementation": "CPython",
    "python_version": "3.12.12",
    "scikit_learn_version": "1.7.1"
  },
  "schema_version": 1,
  "scope": {
    "bootstrap_intervals_are_not_population_confidence_intervals": true,
    "no_population_inference": true,
    "primary_dataset": "UCI HTRU2",
    "transfer_dataset": "UCI Rice (Cammeo and Osmancik)"
  },
  "study_id": "uci-htru2-rice-logistic-random-forest-v1",
  "verification_scope": {
    "claim": "byte identity in the recorded reference environment only",
    "cross_platform_byte_identity_claimed": false,
    "current_artifact_environment": "the reference_environment object above",
    "recommended_release_environment": "a pinned Linux publication environment; these artifacts must be regenerated there before they may be described as Linux-generated"
  }
}