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jev-calibration-audit

tapesymbolstate/jev-calibration-audit

Independent API-only calibration audit of TypeSafe AI's Jev decision model.

Calibration & Research1.00Runner-up: Classification & RoutingQuestionnaire
Automated README summary

Automatically summarized from the README on 14 Oct 2026; not a run by jevbooks. Run instructions and author-reported outcomes still need verification.

What it is

An independent audit measuring the calibration of TypeSafe AI's Jev, a decision model that answers pre-defined questions over a text state with probability distributions. It tests what the returned probabilities mean across domains, languages, and option formats.

How it uses Jev

Jev is queried via public HTTP calls with a state and typed questions (Choice, Score, Noul) to obtain calibrated probabilities. The audit uses these probabilities to compute calibration metrics (ECE, Brier, Murphy decomposition) and to test coherence, invariance, interference, and hedging. Results are recorded per call.

Primitives:choicescorenoul

Technique worth stealing

Report ECE against a noise floor, not zero, and include a state-blind baseline in every set.

Try it

uv sync; cp .env.example .env; fill JEV_API_KEY; uv run python -m jev_audit.preflight

View on GitHub

Start using Jev: API key and your first request →

Model judgments from README excerpts

Project signals use repository metadata, an existing summary and the first 700 README characters, not the full project. “Not found” means not detected in that material; it does not establish absence. These are the original judgments with recorded models and dates, not source audits or run results.

Models & evaluation dates

Inclusion gate
jev-1.13.0
Project signals
jev-1.13.0
Category
jev-1.13.0
Pattern tags
jev-1.13.0

Evidence

These signals use repository metadata, an existing summary and at most 700 cleaned README characters. ≥ 0.60 means reported in that excerpt; ≤ 0.40 means not found there. The middle band is inconclusive. None is a source-code audit or a test result. The runnable-tool question excludes research experiments; the recommendation question asks for a learning shortlist, not a quality verdict.

  • Jev is core to the projectFound in material0.87
  • Shows a System One patternnot found in the excerpt0.18
  • Describes handling uncertaintynot found in the excerpt0.05
  • Reports measured numbersnot found in the excerpt0.28
  • Is a runnable toolnot found in the excerpt0.07
  • Top-10 learning shortlist signalnot found in the excerpt0.20
  • Is a replica of the modelnot found in the excerpt0.03
  • Solves a common problem (0–2)score on a 0–2 scale1.07 / 2
  • About JevFound in material0.99
Signals
Jev is core to the project0.87Shows a System One pattern0.18Describes handling uncertainty0.05Reports measured numbers0.28Is a runnable tool0.07Top-10 learning shortlist signal0.20Is a replica of the model0.0300.51Solves a common problem (0–2)1.07 / 2012

no-judgment band (0.40–0.60)

Design patterns
Questionnaire0.70Check-up0.51Inspection0.32Flight recorder0.2800.51

no-judgment band (0.40–0.60)

The Jev model and date for each judgment stage are listed above. Card written by DeepSeek V4.1 Flash from the README on 14 Oct 2026.