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name: aline_d_estimator description: Solve the ALine-D pairwise linear system to predict OOD accuracies from ID accuracy and unlabeled agreement statistics.

ALine-D Estimator

Use this skill after agreement statistics and an agreement-line slope are available. It implements the paper's ALine-D estimator rather than a simple plug-in baseline.

Inputs

• Statistics JSON from agreement_statistics.
• Fit JSON from agreement_line_fit.

Outputs

• Predicted OOD accuracy per model.
• ALine-S baseline predictions.
• Equation count and residual diagnostics.

Workflow

1. Build one linear equation for every unordered model pair.
2. Use the fitted agreement slope and pairwise agreement terms from Equation (6).
3. Solve the least-squares system over probit OOD accuracies.
4. Convert predictions back to probability space.

Validation

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

Limitations

At least three models are required. Rank-deficient synthetic cases may fail because the system cannot identify every model's OOD accuracy.