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jevcal

abhixhek/jevcal

Calibrate, threshold, and drift-check typed decision models against an LLM teacher.

Evaluation & Benchmarking0.53Runner-up: Classification & RoutingFunnel
Automated README summary

Automatically summarized from the README on 20 Sept 2026; not a run by jevbooks. Run instructions and author-reported outcomes still need verification.

What it is

jevcal measures a typed decision model on your labeled data, picks per-question confidence thresholds to meet your accuracy target, reports escalation traffic, and fails CI on drift. Built for Jev and any model returning answers with probabilities.

How it uses Jev

Jev answers typed questions (Choice, Score, Noul) on your state. jevcal runs the model over your dataset, saves predictions, then compiles thresholds from confidence measures like top_prob, margin, entropy, or the API's confidence. The lock file and report show accepted accuracy, handled share, ECE, and cost split.

Primitives:choicescorenoul

Technique worth stealing

Pick thresholds on one half of your data and verify on the other half; optionally require the 95% lower confidence bound to clear the target.

Try it

pip install "git+https://github.com/abhixhek/jevcal" then jevcal demo

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 projectunclear0.58
  • Shows a System One patternunclear0.56
  • Describes handling uncertaintyFound in material0.89
  • Reports measured numbersFound in material0.96
  • Is a runnable toolFound in material0.67
  • Top-10 learning shortlist signalFound in material0.61
  • Is a replica of the modelnot found in the excerpt0.06
  • Solves a common problem (0–2)score on a 0–2 scale1.48 / 2
  • About JevFound in material0.96
Signals
Jev is core to the project0.58Shows a System One pattern0.56Describes handling uncertainty0.89Reports measured numbers0.96Is a runnable tool0.67Top-10 learning shortlist signal0.61Is a replica of the model0.0600.51Solves a common problem (0–2)1.48 / 2012

no-judgment band (0.40–0.60)

Design patterns
Funnel0.96Check-up0.67Questionnaire0.56Flight recorder0.55Grey zone0.54Traffic light0.44Question bank0.28Ghostwriter0.2500.51

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 20 Sept 2026.