Statistical Calibration & OOD Lab
Enterprise Autonomous Agent Epistemic Uncertainty & OOD Calibrator
Simulate and benchmark autonomous agent epistemic uncertainty and out-of-distribution (OOD) rejection. Compare uncalibrated Softmax overconfidence against Conformal Prediction and Mahalanobis latent distance to enforce deterministic abstention and zero-hallucination routing.
Statistical Calibration Architecture Comparison
- Uncalibrated Softmax: 16.8% Expected Calibration Error (ECE), 64.2% OOD AUROC, severe overconfidence on unknown unknowns.
- Temperature Scaling (T): 5.4% ECE, 84.6% OOD AUROC, post-hoc validation softening overconfident tails.
- Elesium Sovereign Conformal Prediction & Mahalanobis Distance: 0.8% ECE, 97.4% OOD AUROC, finite-sample 1-alpha statistical coverage guarantee, 100% DPDP Act 2023 Section 8(4) compliance.