Medical and health triage (non-diagnostic) with decision models

UiPath prior-authorisation triage agent with a Jev guardrail that measures and records PII crossing the model boundary without masking.

Open clinical text classifiers (0.8B-9B on Qwen3.5) with labels set at inference time, run locally and compared with Jev 1.13.

Pre-registered study testing Jev's calibration claims on clinical diagnosis cases against Claude Opus 5 and Opus 5.5.

Evaluation of Jev versus DeepSeek and Qwen on healthcare decision tasks: triage, diagnosis, medication, nursing and trial screening.

TLA+-verified consensus kernel around Jev that may escalate but never returns a confident wrong verdict, tested on 1,680 pharmacy cases.

Rust research workbench where Jev gives a cancer-of-unknown-primary origin distribution over 22 classes, gated locally for review.

Spanish oncology decision-support prototype that walks ESMO guideline trees and uses Jev only for judgment calls.

Research implementation of Jev-style typed decisions over clinical evidence: supported, contradicted or unresolved.

Jev-inspired PyTorch research framework that encodes an overnight sleep recording once and answers many Choice, Noul and Score questions.

Medplum demo where a bot uses Jev to compare a provider's visit note with a discharge summary and flag agreement or potential conflict.

Small web demo that makes clinic triage decisions with Jev, falling back to heuristics when no key is set.

Experiment screening ADHD review abstracts as include or exclude with Jev, scored against Cohen et al. 2006 abstract triage labels.

Two frozen open models answer yes/no per exam option; their agreement drives an auto-release gate and a conformal candidate set.

Research framework for biomedical decision models on Qwen3.5, studying domain pretraining, NLI training, calibration and abstention.

100-question-per-cell check of Jev on Korean versus English reading, paraphrase and medical exams, with recorded responses.

Pre-registered benchmark of Jev as a medical hallucination check on MedHallu, versus fast LLMs, on accuracy, latency and cost.

Jev-style medical QA on Qwen3.5-4B that picks the answer option in one forward pass instead of generating text.

Benchmark of Jev versus OpenAI structured outputs extracting smoking history from 1,000 synthetic notes.