Silence Is Safety: A Calibrated Clinical NLI Verifier for MedNLI

This preprint presents AetherMind MedNLI Clinical NLI Verifier, a calibrated clinical natural-language inference model for the MedNLI benchmark. The model performs three-way inference over clinical premise-hypothesis pairs: entailment, neutral, and contradiction. On the MedNLI test split, the verifier achieves 88.19% accuracy with 95% confidence interval [86.50 89.87], macro F1 of 88.21%, contradiction recall of 92.41%, and contradiction precision of 93.99%. Temperature scaling fitted on the development split improves expected calibration error from 0.090 to 0.037. The paper also evaluates selective abstention for safer clinical claim verification workflows.