This is an independent community listing. Check the source, license, data handling, and evaluation caveats before relying on a project. Inclusion is not an endorsement or security review.
Independent Jev-1.13.0 audit with reproducible code and per-call JSONL: tests abstention options, matched Korean and English items, question-shape interference, and option order; its strong abstention finding is on the KoBBQ dataset, not a universal calibration guarantee.
Early Python toolkit and CLINC150 study of conformal routing thresholds and prediction-powered audits over Jev 1.13 through OpenRouter, with request plans, 2,412 journalled answers and usage records, analysis code, and tests; its per-incoming-query risk bound depends on matching calibration and deployment traffic, and the study shows the scope gate missing its target after out-of-scope prevalence shifts while fallback accuracy remains unmeasured.
Calibration check on inputs whose true probability is fixed by construction (hidden fair dice, coins, four-way spinners) and on synthetic forecast documents, with raw responses and offline recomputation; Choice put 82.9% on face 1 across all 400 rolls at 19.0% accuracy and turned a stated 30% risk into 5.3%, while Noul stayed near the truth for 2 to 4 options and reported 15 to 17% for 8 to 20 options; no comparison with other models and no realistic task set, so it shows how far the probabilities can drift when the input carries no evidence rather than how Jev ranks against alternatives, run in launch week against jev-1.13.0.
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