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prediction_table_contracts

prediction_table_contracts

Validate agreement-on-the-line prediction tables while separating estimator inputs from evaluation-only OOD labels.

Independent GitHub snapshot · Automated classification · Original documentation governs

Skill-Dokumentation

GitHub

name: prediction_table_contracts description: Validate agreement-on-the-line prediction tables while separating estimator inputs from evaluation-only OOD labels.

Prediction Table Contracts

Use this skill when preparing inputs for agreement-on-the-line or ALine-D recovery experiments. Do not use it for probability-score methods that require softmax confidences rather than class predictions.

Inputs

  • JSON table with models, id_labels, id_predictions, ood_predictions, and optional ood_labels.
  • At least three models are required for ALine-D.

Outputs

  • Normalized JSON table with deterministic model ordering.
  • Metadata for model/sample counts and a flag showing OOD labels are evaluation-only.

Workflow

  1. Validate unique model identifiers and consistent prediction lengths.
  2. Require every model to have ID and OOD class predictions.
  3. Store optional OOD labels under evaluation_only.
  4. Reject attempts to treat OOD labels as estimator-visible fields.

Validation

Run python tests/test_prediction_table_contracts.py from this skill directory.

Limitations

This skill validates table structure only; it does not compute agreement statistics or accuracy predictions.

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