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jev-deferred-crispification

dnakhoa/jev-deferred-crispification

Position paper: missing Hidden-Markov and fuzzy primitives in Jev.

Calibration & Research0.97Runner-up: Agent DecisionsScorecard
Automated README summary

Automatically summarized from the README on 30 Sept 2026; not a run by jevbooks. Run instructions and author-reported outcomes still need verification.

What it is

A position paper and reference architecture (BSF-S1) for TypeSafe AI's Jev/System-One decision models. It identifies two missing primitives—Hidden-Markov belief over latent regimes and fuzzy membership for borderline predicates—proves two lemmas, and provides weight-free audit metrics (TCE, AMS) for practitioners.

How it uses Jev

The README does not describe using Jev directly; it critiques Jev's design and proposes extensions. Jev's typed decisions (Choice, Score, Noul) are discussed as lacking Hidden-Markov belief and fuzzy membership, but no code example shows Jev being called.

Primitives:choicescorenoul

Technique worth stealing

Deferred Crispification: collapse structure only once at the actuator, not per hop.

Try it

git clone https://github.com/dnakhoa/jev-deferred-crispification && cd jev-deferred-crispification && python3 experiments/run_all.py

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 material0.85
  • Shows a System One patternFound in material0.75
  • Describes handling uncertaintynot found in the excerpt0.08
  • Reports measured numbersnot found in the excerpt0.17
  • Is a runnable toolnot found in the excerpt0.12
  • Top-10 learning shortlist signalnot found in the excerpt0.17
  • Is a replica of the modelnot found in the excerpt0.24
  • Solves a common problem (0–2)score on a 0–2 scale1.06 / 2
  • About JevFound in material0.96
Signals
Jev is core to the project0.85Shows a System One pattern0.75Describes handling uncertainty0.08Reports measured numbers0.17Is a runnable tool0.12Top-10 learning shortlist signal0.17Is a replica of the model0.2400.51Solves a common problem (0–2)1.06 / 2012

no-judgment band (0.40–0.60)

Design patterns
Scorecard0.74Check-up0.43Grey zone0.2900.51

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 30 Sept 2026.