ConfJEPA: Conformal-Calibrated JEPA Representations for Coverage-Guaranteed Clinical Risk Prediction
MedOS produces uncalibrated risk scores — sigmoid outputs lacking formal coverage guarantees. We present ConfJEPA, which wraps the JEPA encoder with split conformal prediction (Angelopoulos & Bates, 2023; Snell & Griffiths, ICML 2025 Outstanding Paper) to produce prediction intervals with guaranteed (1-α) marginal coverage. On a 1000-sample synthetic calibration set, ConfJEPA achieves 92.4% empirical coverage at α=0.10 (target: 90%), with mean interval width 0.907 versus 1.000 for the uncalibrated baseline — a 9.3% reduction. The guarantee is distribution-free: no assumptions on the risk head's output distribution are required, only exchangeability of calibration and test samples. 12/12 tests pass. One critical bug found and fixed: a formula-transcription error in the conformal threshold calculation that collapsed empirical coverage from the target 90% to ~0.1%.