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jev-survey

evan-py-chen/jev-survey · Homepage

Survey of Jev-style typed decision models: prior work, adaptation costs, evidence.

Classification & Routing0.58Runner-up: Calibration & Research
Automated README summary

Automatically summarized from the README on 26 Oct 2026; not a run by jevbooks. Run instructions and author-reported outcomes still need verification.

What it is

A short academic survey (ACM SIGKDD Explorations, 2026) for researchers and practitioners on typed decision models that return probability distributions over closed answer sets instead of generating text, covering their origins, adaptation costs, and empirical evidence.

How it uses Jev

The README does not describe using Jev in code; it is a survey. It discusses the interface where a state plus a call-time question yields a probability distribution over a closed answer set, and recommends testing a typed model against a label-probability readout on an open model and a cheap generative cascade.

Primitives:choicescore

Technique worth stealing

Compare a typed decision model against a label-probability readout and a cheap generative cascade, using the deployment's own acceptance rule.

Try it

Build the PDF: cd src && tectonic -X compile main_kdd.tex, or use pdflatex/bibtex.

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 projectunclear0.57
  • Shows a System One patternnot found in the excerpt0.16
  • Describes handling uncertaintynot found in the excerpt0.05
  • Reports measured numbersnot found in the excerpt0.03
  • Is a runnable toolnot found in the excerpt0.04
  • Top-10 learning shortlist signalnot found in the excerpt0.14
  • Is a replica of the modelnot found in the excerpt0.11
  • Solves a common problem (0–2)score on a 0–2 scale1.89 / 2
  • About JevFound in material0.99
Signals
Jev is core to the project0.57Shows a System One pattern0.16Describes handling uncertainty0.05Reports measured numbers0.03Is a runnable tool0.04Top-10 learning shortlist signal0.14Is a replica of the model0.1100.51Solves a common problem (0–2)1.89 / 2012

no-judgment band (0.40–0.60)

Design patterns
Funnel0.50Ghostwriter0.44Check-up0.3500.51

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 26 Oct 2026.