pytest-jev: semantic assertions for LLM tests

Evaluates decision probabilities on labeled examples and compares accuracy, calibration and automation coverage. It helps choose when to accept Jev decisions or escalate them, and supports regression checks when model behavior changes.

Adds diagnostic and routing judgments to OpenTelemetry log records. Jev helps identify records worth further model analysis while retaining the original archive, separating triage decisions from long-form diagnosis.

An independent API-based audit of Jev that examines how confidence relates to observed correctness, including experiments with abstention. The published scripts and results are research evidence, not a guarantee for other datasets.