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zh-decision-bench

CodyQin/zh-decision-bench

First Chinese calibration benchmark for Jev-class decision models.

Evaluation & Benchmarking0.49Runner-up: Calibration & Research
Automated README summary

Automatically summarized from the README on 24 Oct 2026; not a run by jevbooks. Run instructions and author-reported outcomes still need verification.

What it is

A benchmark measuring accuracy and probability calibration of 'System One' decision models on Chinese tasks, covering routing, urgency, escalation, and scam detection, with a public CC BY 4.0 dataset and evaluations of five models.

How it uses Jev

Jev is evaluated as one of five models: it answers typed choice, score, and noul questions on Chinese task states, and its returned probabilities are scored for accuracy, ECE, and robustness to option order and zh-CN/zh-TW variants.

Primitives:choicescorenoul

Technique worth stealing

Evaluate calibration (ECE, NLL) alongside accuracy, and test robustness to option order and script variants.

Try it

Load the dataset with `load_dataset("CodyQin/zh-decision-bench")`; run scripts like `python src/refit.py` for temperature refit.

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-1.14.0
Project signals
jev-1.14.0
Category
jev-1.14.0
Pattern tags
jev-1.14.0

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 material0.78
  • Shows a System One patternnot found in the excerpt0.14
  • Describes handling uncertaintynot found in the excerpt0.03
  • Reports measured numbersnot found in the excerpt0.08
  • Is a runnable toolnot found in the excerpt0.07
  • Top-10 learning shortlist signalnot found in the excerpt0.26
  • Is a replica of the modelnot found in the excerpt0.14
  • Solves a common problem (0–2)score on a 0–2 scale1.06 / 2
  • About JevFound in material0.99
Signals
Jev is core to the project0.78Shows a System One pattern0.14Describes handling uncertainty0.03Reports measured numbers0.08Is a runnable tool0.07Top-10 learning shortlist signal0.26Is a replica of the model0.1400.51Solves a common problem (0–2)1.06 / 2012

no-judgment band (0.40–0.60)

Design patterns
Check-up0.3900.51

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 24 Oct 2026.