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Jev for Healthcare & Life Sciences

9 curated Jev resources. Healthcare, life sciences, and clinical workflows.

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  • Docs2
  • Repos & sites7

All 9 Jev resources for Healthcare & Life Sciences

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9 resources

Intake Router
A clinical intake router that picks a care pathway from a patient's reported reason for contact and flags whether the message needs a same-day response, without ever assigning a condition or a treatment.
Jev Tools & CLIs#community#python#healthcare
Community
Jev-MedQA
2GitHub stars
Jev-style medical QA implementation on Qwen3.5-4B that selects an answer from candidates in one forward pass instead of generating text. It reports 69.42% accuracy versus 67.41% for standard generation and a 10.37x speedup across 153,889 questions from nine benchmark sets.
Jev Models & Reimplementations#community#medical#benchmark
CommunityZtrura/Jev-MedQAPython
jev-medhallu-benchmark
2GitHub stars
Pre-registered benchmark adding Jev 1.13 to Stanford MedHELM's MedHallu results: one Noul asks whether a proposed answer misrepresents its PubMed abstract. Jev scored 92.9% on 1,000 test items at a 204 ms median and USD 0.03 per 1,000 checks through OpenRouter.
Jev Benchmarks & Evaluations#community#medical#hallucination
Communitystperic/jev-medhallu-benchmarkPython
jevextract
1GitHub stars
Grounded information extraction library: deterministic code proposes candidate spans with exact offsets and Jev answers one Choice per span plus sentence-level Nouls, so every extraction is a substring of the source. Ships a bilingual benchmark and paper.
Jev Tools & CLIs#community#information-extraction#nlp
Communitygabazureus/jevextractPython
JevSpan
6GitHub stars
Zero-shot named entity recognition library on Jev: text is split at punctuation, candidate windows are offered as one Choice question per entity type, then verified and boundary-polished by further Choice calls. Types are defined in plain words; no training data or GPU is needed.
Jev Repos & SDKs#community#ner#extraction
Communitylzq-0529/jev-spanPython
Vector Graph RAG
255GitHub stars
Graph RAG framework over Milvus vector search with no graph database required: Jev Noul judgments select graph relations and rerank full source passages alongside vector-search candidates, reaching 86.07% average Recall@5 on 1,000 MuSiQue and 1,000 2Wiki queries in the two-stage evaluation.
Jev Integrations & Adapters#community#rag#retrieval
Communityzilliztech/vector-graph-ragPython
Paper Trellis Citation Verifier
10GitHub stars
A browser tool that checks whether a cited paper supports the sentence citing it: code matches references and verifies quotes, Claude proposes an evidence passage, and Jev scores supports, contradicts, or says nothing.
Jev Tools & CLIs#community#javascript#browser
CommunityMarissaFamularo/citation-verifierJavaScript
Cookbook: Guardrails for LLMs
Screen every message going into and out of an LLM app: a Noul describes possible hazards, a Score rates severity, and code thresholds the probabilities.
Jev CookbooksDocs#official#cookbook#guardrails
Official
Cookbook: Hierarchical Classification
Classify documents through deep patent, retail product, biomedical, and source-code hierarchies using parallel beam search over Choice probabilities.
Jev CookbooksDocs#official#cookbook#classification
Official

Related industries

Industries that overlap with Healthcare & Life Sciences.

Jev articles

Original guides that go deeper on Jev healthcare & life sciences.

All Jev articles
Designing the State: What to Include and What to Drop
Most Jev accuracy problems are state problems. What belongs in a state, what is a pre-made judgment to leave out, and why naming the slice you ask about matters more than the wording.
Jev Practices & Patterns#state#design#primitives
Read article
Guardrails and Prompt Injection: Hardening the Typed Answer
A decision model cannot be talked into generating text, but the label is still a target. Why narrow, literal questions resist injection and why keeping the act in code is the real backstop.
Jev Practices & Patterns#guardrails#security#prompt-injection
Read article
Jev in Customer Support: Triage, Routing, and Escalation
Support is a long chain of small judgments over text. Triage category and urgency separately, route with a confidence gate, decompose hard tickets, and decide the action in code.
Jev Practices & Patterns#customer-support#routing#triage
Read article

Watch: Jev in action

Video walkthroughs and demos from the community.

YouTube: Albert Olgaard tests Jev and explains why System One models matter.

YouTube: Hunter Bohm on pricing, parallel decisions, whether Jev is actually new, and his own Astra plus Jev benchmark.

YouTube: Moritz builds three prototypes: a voice-controlled browser, memory retrieval, and a YouTube topic scorer.

Discussions about Jev

Threads from Reddit and Hacker News about building with Jev.

Hacker News: Qualitative researchers classifying participant free text with Jev at negligible cost.

effisfor13 pointsI was impressed by Jev, please explain why I shouldn't beRead the thread on Hacker News

Hacker News: Show HN for public Minecraft PvP where a diffusion LM picks moves from structured state.

2 pointsShow HN: Minecraft PvP against DiffusionGemma-as-Jev, 24 ms per decisionRead the thread on Hacker News

Hacker News: A one-token logprob wrapper that also classifies webcam frames.

allanrbo151 pointsA single function Jev-like wrapper for LLMs, including vision modelsRead the thread on Hacker News

Hacker News: Privatemode compares GLM-5.3-Flash typed decisions with Jev on latency, cost, and accuracy.

flxflx129 pointsTurning GLM-5.3-Flash into a Jev-like decision modelRead the thread on Hacker News

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