Calibration and threshold setting with decision models

Resume-to-JD screening study (Chinese) with 5 Noul gates, 4 Score dimensions and a routing Choice per request, hardened over three versions.

Local reproduction of Jev-style inference that reads option-token logits from a small LLM in one pass, with an honest failure log.

Small Jev measurement bench with an append-only call log, labelled claims and a stated negative result.

Harness that runs Jev on all 19,646 TMMLU+ Traditional Chinese questions as four-way Choices, reporting accuracy and calibration.

Tool that recomputes Jev's confidence identities on outputs published in public repositories to spot answers Jev never actually produced.

RPG experiment pitting Jev against OpenAI's Decisions API as NPCs, comparing wins, per-move accuracy, calibration and cost.

Korean study notes and TypeScript mock-ups of Jev concepts, with a local Laya versus GPT-5 comparison and a calibration toolkit.

Benchmark harness pitting Jev against Claude Sonnet 5 and Haiku 4.5 on Banking77 intent sorting with a confidence gate.

Offline Python toolkit that measures sensitivity, Fisher information and information loss in the probabilities of Jev-style agent systems.

Research code showing that short, natural-looking context additions can flip decision models like Jev to a chosen wrong answer.

Research fork of Laya that reads typed choice and yes/no decisions from an image plus optional text in one forward pass.

Open decision models that derive calibrated confidence from recurrent looped-layer dynamics instead of RL, with early exit and a Jev API.

Research adding plain-English constraints to JEPA world-model planning, with Jev judging each imagined step instead of an LLM.

Research implementation of Jev-style typed decisions over clinical evidence: supported, contradicted or unresolved.

Local Jev-style decision model on Qwen3.5-4B with four stress tests that show where one-pass decisions break.

LogitTrail (formerly Mini Jev): local workbench that reads typed Choice, Noul and Score decisions from a frozen LLM's logits.

Reproduction and stress test of a paper asking whether Jev-style probabilities stay calibrated after routing on selected examples.

Open System-1 (OpenJev): Apache-2.0 research models giving calibrated per-option probabilities, best is a 4.9B exp9a.

openvons (open-Jev): finite-choice decision layer for text, images and Japanese voice, with a none option and execute/confirm/reject.

Pandu: tiny local policy networks (2.9K-5K parameters) with calibrated uncertainty that fall back to a teacher when unsure.

Laptop-scale reimplementation of RL for Calibrated Decisions: parallel constrained decoding trained with GRPO and a Brier reward.

Stdlib-Python guardrail and model router for LLM gateways on Jev, with an independent accuracy, calibration and latency evaluation.

Static charts comparing Jev with 110 other models on Thai standardized exams for accuracy, cost, speed and calibration.

Lightweight reproduction of the Jev shape on a ModernBERT encoder and a diffusion LLM, comparing speed, accuracy, calibration and cost.

Write-up with measurements on calibrating Jev as a code reviewer: context effects, textual tells, thresholds and noise near thresholds.

Local System One-compatible server that reads option probabilities from a small MLX LLM, with measured calibration.

Self-hostable calibrated decision model for images and text (Qwen3-VL-4B + LoRA) scoring 82.7 percent on public JevBench.

Rust library and CLI for compound decisions: ask Jev small questions, combine answers with rules in a YAML/JSON decision graph.

Composable Python toolkit for Jev: question builders, confidence gates, batch evaluator, calibration, CLI, MCP server and agent skill.

Effect library turning Jev Choice, Noul and Score answers into typed branches with a compiler-enforced Uncertain case.