New resources

Controls information and surface cues to distinguish Jev answer confidence from self-knowledge; black-box behavior does not establish access to an internal knowledge state.

Shared evidence encoding and candidate-probability readout, trained with representation and action-outcome feedback. Results remain author-reported.

English/Arabic persona-conditioned Jev survey audit; the effects concern simulated respondents in one model, not measurements of real populations.

Checks statement support in both directions between generated and reference radiology reports; agreement depends on report size and error scope, and a specialized comparator remains stronger on clinically significant errors.

Jev injection audit separates probability shifts from attacker-target selections; adaptive attacks are checked on fresh validation calls over reconstructed InjecAgent cases.

Evaluates decision models and confidence-routed LLM cascades on selected zero-shot social-science annotation tasks; lower cost coexists with task-dependent errors and overconfidence.

Retrospective agent-trace risk classification compares Jev with generative judges across four collections; rankings vary by dataset, and latency/cost summarize successful or valid calls.

A small scientific-workflow study separates semantic Choices, computed quantities and final labels; selection errors in comparison models can change intermediate counts without changing the final label.

Preliminary medical-benchmark evaluation of Jev 1.13 reports task-dependent accuracy, calibration and weak unanswerable-question detection; it does not establish clinical deployment validity.

VLM local-goal planning with Jev action selection over mobile accessibility trees; time and cost comparisons are conditioned on successful trajectories.

Jev action selection paired with language-model planning for StarCraft II; concurrent interface changes prevent isolating the planning effect.

Probability-guided context additions redirect initially correct decisions in four systems while preserving questions and options; human validity checks cover only a sampled subset of successful attacks.

Tool-argument judges including Jev reject some correct derived values without visible references; model-generated references are evaluated on three benchmarks.

Combines Jev state tables, sparse flagship-model anchors and human–model discrepancy estimates; scaling a simulated population does not increase the underlying human evidence.

Keeps raw memory records, separating Jev relevance judgments from LLM search planning and answer generation. Results remain author-reported.

Studies underuse of ordinal labels in direct-decision models; finer scales intensify compression, while better accuracy or shuffled option order does not necessarily restore scale utilization.

Tests option-channel attacks on seven open-weight models; reversed decisions can remain confident. The reported experiments do not test hosted Jev.

Confidence-gated Jev control with LLM fallback; gains depend on action alternatives and baseline routing. Results remain author-reported.

Repeated ContractNLI evaluations show that opposing corrections and regressions can leave aggregate accuracy unchanged; consistent answers may remain wrong, while majority-vote gains are small and uncertain.

Controlled same-number citation swaps test Jev source verification; detecting wrong financial roles trades off against accepting equivalent evidence.

Candidate-answer readout during interruptible reasoning, with gates for starting, reading and stopping; results depend on a fixed backbone and task suite.

Knowledge, reasoning and multilingual multiple-choice evaluation of Jev; reported rankings and mathematical weaknesses apply to the selected models and benchmarks.

Jev memory-retirement evaluation separates confirmed updates from suggestions; mixed LLM/human labels, shared errors and selection on a small development set constrain cascade claims.

System One controllers coordinate bounded multi-agent decisions while LLM workers reason; reported efficiency concerns the complete collaboration framework.

Typed-decision classification and verification under content-preserving table rewrites; confidence can indicate instability without establishing correctness.

Structured video decisions with temporal spans and candidate scores; cached and joint inference reuse visual computation. Results remain author-reported.

Shares an image prefix across batched forced-choice questions; reported training gains concentrate on represented task families, and warm amortized execution savings trade off against peak memory.

Overcooked cooperative-game decision policy, with discrete native-action scoring and shared-policy evaluation artifacts.

AgentJev model card documenting a compact state-to-distribution decision interface without free-text decoding.

Open TruthfulQA truthfulness judge checkpoint, relevant to comparing model-derived evaluation labels.

Italian candidate-token decision checkpoint covering moderation and intent-routing tasks; capabilities remain publisher claims.

Bit-Jev distilled model card with bilingual typed-question interfaces and local runtime instructions.

Bonsai-based image-capable decision model documenting soft-label distillation and a decision head.

LoRA checkpoint reproducing the cached causal scoring arm of a public typed-decision experiment.

Code-review triage model returning structured verdicts, risk levels and flags for pull-request diffs.

Verifier-guided training experiment for one-step computer-use form actions on synthetic held-out form signatures.

Controlled decision-head experiment varying data coverage while fixing the training recipe, with held-out transfer evaluations.

Diffusion-model adaptation reading Yes/No logits for typed Choice, Score and Noul decisions.

EmbeddingGemma adaptation for typed questions over support, invoice, security and agent-trace workflows.

Exu decision head for agent and workflow traces, with option scoring and fitted-temperature probabilities.

Granite function-calling checkpoint covering nested, chained and parallel tool calls as a generative comparison baseline.

Arabic operational-workflow decision checkpoint covering tickets, invoices, alerts and agent traces.

Author checkpoint bundle for Jeva with backbone, adapter and decision-head files; weights were not loaded, and the inspected card specifies no model license.

JevEmbed embedding checkpoint with documented Choice, Score and Noul scoring over its training corpus.

Jevons seed adapter for option-token scoring, with typed outputs assembled by the serving implementation.

Vicuna-based JudgeLM checkpoint for evaluating open-ended answer pairs; useful as a generative judge comparison.

Arch-Router checkpoint addressing preference-aware LLM routing rather than general answer generation.

Experimental Kenning decoder variant using constrained answer-token readout behind the System One interface.

Browser-agent fine-tuning experiment for Laya, including reported negative results and reproducibility details.

Encoder-based prompt router that scores user-defined routing lanes in one pass, an adjacent routing baseline.

LightJev candidate-scoring checkpoint for finite-answer English workflow questions, with intended-use boundaries.

Experimental Japanese LLM-jp candidate-token scorer; the card explicitly disclaims demonstrated general Jev-equivalent quality.

Distilled encoder for one fixed coding-agent action schema; the card explicitly limits claims of Jev equivalence.

MD-Judge safety classifier for question-answer pairs, offering an adjacent guardrail and evaluator baseline.

Multimodal mJev candidate-selection checkpoint with visual context, probability outputs and documented runtime.

ModernBERT modality router choosing output modalities for vLLM Semantic Router, an adjacent request-routing artifact.

Japanese ModernBERT cross-encoder for scoring state/question/candidate pairs through a Jev-compatible interface.

Compact Nandi model card describing single-turn tool-call generation, an adjacent alternative to bounded action selection.

Nano-Jev small cross-encoder decision model for RAG pipelines, returning probabilities over supplied candidates.

Open Decider specialist checkpoint with an explicit not-answerable outcome alongside typed answer probabilities.

Independent DeBERTa implementation of typed questions and candidate-probability readout, without claiming original Jev weights.

Thai-English decision model card describing bounded choice, ordered-score and yes/no probability interfaces.

Flight-simulator decision-model project with documented action-selection experiments; not evidence of operational aviation suitability.

Typed decision checkpoint documenting supervised warmup followed by bandit-feedback RLCD and option-distribution outputs.

Qwen adapter for parallel single-token scoring of several schema fields, with candidate-token readout documented.

NLI cross-encoder that maps state/candidate entailment scores to typed answer distributions.

Russian specialist decision checkpoint limited to the translated benchmark's workflow schemas, with distributions for each answer.

CPU request classifier predicting routing signals such as task category, difficulty and stakes for an LLM router.

Schema-conditioned DeBERTa scalar scorer with deterministic grouping into Choice, Noul and Score answers.

Gated decision-head study distinguishing commitment, alternatives and abstention over supplied choices.

Multimodal StartLux decision checkpoint with typed questions, bounded image inputs and candidate probabilities.

Distilled DeBERTa model using teacher-generated supervision for typed routing, classification and gating questions.

QLoRA single-pass decision-scorer experiment with held-out calibration reporting and explicit independent-project scope.

Small local System One-compatible model using option-restricted next-token scoring and documented synthetic training splits.

MiniLM router selecting image-compression techniques from natural-language queries, an adjacent task-specific routing example.

Independent Tiny-Jev implementation documenting typed probabilities and its separation from TypeSafe's weights and code.

Workflow-specific classifier heads over a frozen MiniLM encoder; the card explicitly identifies supervised specialist scope.

Turkish typed-decision checkpoint with shipped temperature scaling; its card flags test-informed training and worsening support-task calibration. Weights were not loaded or independently evaluated.

Turkish System One checkpoint using candidate-letter probabilities for finite-option questions.

W1 diffusion-model card documenting structured decision tasks and comparison artifacts, with publisher-reported performance.

Burmese XLM-RoBERTa decision model with Choice, Noul and Score questions and per-answer probabilities.

Task-separated agent-state training with gold and teacher targets; raw trajectories and some training sources are omitted, with noncommercial terms stated.

Recorded agent states, answer keys and model outputs; L1 question texts are omitted, and closed-loop evaluation requires the separate harness and live models.

Public browser-task sample from AIMultiple's decision-model evaluation, with task definitions and comparison provenance.

Bilingual audio-instruction alignment benchmark with positive examples and difficult negative pairings.

Audio-judge training corpus with decomposed binary rubrics, JSON answers and per-item evidence.

Audio-window decision dataset with source annotations and categorical targets, separating gold from teacher-generated labels.

Frozen BazaarBench semantic-judge run documenting the exact judge configuration and behavioral-evaluation artifacts.

Berkeley Function Calling Leaderboard's function-call evaluation cases, an adjacent tool-selection and execution reference.

Small BFCL-derived next-tool/no-function routing pilot, explicitly not a complete function-calling leaderboard benchmark.

WANLI comparison archive distinguishing independently measured smaller-model results from cited larger-model numbers.

Typed questions retaining upstream human labels and teacher/rater-derived soft targets, including a documented correction that swaps teacher probabilities on mismatched answers.

CITY-Jev perturbation benchmark for agent action selection, step judging, outcome verification and safety decisions.

Chinese typed-decision test cases and scoring eligibility; related rows can share parent material, while contamination and cross-domain overlap remain incompletely audited.

Chinese typed-decision training/validation mixtures with provenance; source tasks are imbalanced, some labels are model-generated, and source-specific restrictions remain.

Multi-domain ClassOne curriculum of structured Choice, Noul and Score questions for decision-model training.

Typed questions about individual source-code functions for training and evaluating code-understanding decision heads.

Coding-agent routing states and outcomes on Terminal-Bench; this is a single-trial-per-task/arm run archive, not a newly independent task benchmark.

Aggregate Jev and self-judging Gemma confidence statistics from a retrieval benchmark, including unsuccessful pipeline results.

Archived Darwin decision-model run on a pinned Decision Index suite, including requests, results and reproduction metadata.

JudgeLM training and validation examples for teaching models to judge paired open-ended answers.

Synthetic Decida training questions with probability-distribution labels across Choice, Noul and Score tasks.

Multilingual synthetic typed tasks with soft labels and repeated states per task in the Jev-compatible schema.

Catalog of benchmarks used by decision-model publishers, relevant to evaluating coverage and comparison choices.

Recorded Core AI model runs on a fixed public JevBench subset, with local execution and harness provenance.

Frozen manifests and raw outputs comparing Jev, Laya and Julia on identical decision questions.

Guardrail evaluation cases for harmful content, prompt attacks, denied topics, filtering, PII and grounding decisions.

Argument-level evaluation sets with correctness/path labels and a source-relocation control; derived from existing benchmarks and model trajectories, not an independent new task population.

EdgeIntent benchmark pairing edge-service requests with typed intent contracts for orchestration studies.

Original FOMC annotation records for social-science decision studies, with missing labels explicitly retained as unlabeled.

Traditional-Chinese benchmark result archive recording option permutations and mapped predictions; question text remains in the upstream labeled datasets.

Decision-oriented corpus derived from public agent trajectories for tool selection, routing and local agent control.

Retired ToolEmu and AgentDojo raw evaluation traces, retaining failures and partial runs rather than claiming validated final scores.

Sanitized public-log triage benchmark evaluating whether log lines should be escalated to a reasoning model.

Frozen-candidate RAG comparisons of Jev reranking, a cross-encoder and no reranker, with per-query artifacts.

Chinese reranking run archive on public hard-negative retrieval queries, comparing Jev question primitives with a lexical baseline on shared relevance labels.

Synthetic robotics-control replay data for a Jev-like project, with source provenance and stated physical-validation limits.

Synthetic alert stream comparing Jev and a reasoning model as PagerDuty triggers, without production traffic claims.

Arabic intent-routing evaluation across standard, dialectal and mixed language slices, plus unseen-domain RAG tests.

Turkish machine translation of Jev-bench with preserved labels, pinned source revision and translation manifest.

Multiple-choice evaluation set designed to score option probabilities rather than generated answer strings.

CVE-to-CWE finite-choice benchmark studying vulnerability-class selection with a larger candidate set.

Visual-choice benchmark with source-derived labels and model-written distractors, not fully human-verified; both option lists place the gold answer first and require shuffling with label remapping.

English-Thai governance decision cases about execute, ask-user, reject, review and risk judgments.

Synthetic structured states and labeled options for training single-letter Tev/Jev-style decision models.

Synthetic incident hierarchy testing tree-based selection beyond Jev's per-question choice limit.

JevAdvBench adversarial test data for typed decision models, covering clean requests and attacks.

JEVal benchmark data for comparing general decision models beyond Jev, accompanying its empirical study.

English, Turkish and German decision-training data supporting the JevAlt model family.

Metamorphic coherence benchmark checking relationships among typed probability predictions rather than accuracy alone.

JevBench framework cases and model predictions on matched inputs from public datasets.

Benchmark Heaven's decision-model results and scoring-method documentation for calibration, accuracy and runtime comparisons.

JevEmbed training and evaluation questions with request/answer JSON fields and documented source splits.

Jevhome training corpus of typed state/question pairs with teacher-provided gold answers and probabilities.

JevJudge multimodal agentic-judge evaluation data, released with evaluation-only and upstream-license restrictions.

Robotics-judge evaluation with blank-media, shuffled-media and permuted-option controls, disclosing human and construction-based labels plus text-shortcut risks.

JudgeBench test data evaluating LLM judges on objective correctness judgments.

Korean finite-choice benchmark assembled from public datasets, with normalized options and baseline provenance.

Korean decision benchmark combining reasoning, language, tool use and preference tasks with probability outputs.

Matched Laya/Jev comparison artifacts that examine limitations of cross-benchmark performance claims.

English and Arabic System One research draft that explicitly notes pending independent linguistic and label review.

Multimodel reasoning-response export for next-JEV training; explicitly a CoT-only release without classification targets.

Frozen NOTAM typed-question evaluation suites with calibration analysis; explicitly restricted from operational aviation use.

NVIDIA function-calling RL data reformulating expert tool-use steps as behavior-cloning decisions.

Per-item classification and routing predictions comparing Jev, Laya and other stacks on matched inputs.

Procedurally generated typed questions with reference probability distributions defined by the generator.

Synthetic Pythonic function-calling examples for tool-use training, an adjacent generative baseline resource.

RANIntent benchmark mapping natural-language network intents and telemetry to typed O-RAN policy decisions.

Published raw reward-model benchmark scores supporting reanalysis of evaluator behavior.

RewardBench preference-pair evaluation data covering chat, safety and reasoning comparisons for reward models.

RewardBench 2's distinct harder evaluation set, including unseen human data and additional reward-model test categories.

RLCD decision training data with finite-option questions and calibration-oriented supervision.

Published RSI-Jev benchmark runs with raw Decision Index outputs and run documentation.

Russian LLM-judge dataset documenting collected model judgments, relevant to multilingual evaluation supervision.

SearchJev training and evaluation release for search-agent decisions, with versioned split and quality-sidecar documentation.

Teacher-probability targets for SII-Decision training, with validation and source manifests; targets are model-derived, and upstream data licenses vary.

Synthetic specialist-training and development decisions for multiple business workflows in a Jev-compatible format.

Social-science classification codebooks defining labels and meanings for probabilistic annotation studies.

Frozen data and results accompanying a survey of semantic decision engines in network-control loops.

Fictional support-ticket routing cases under a written policy, with held-out model predictions.

Fictional support-urgency cases with explicit yes/no criteria and recorded model probabilities.

Small synthetic structured-state reasoning diagnostic; explicitly not a population benchmark or blinded leaderboard.

Deterministic synthetic intervention diagnostics for System One Mini, without real agent traces or teacher-model labels.

Rule-labeled synthetic System One Lite data, including IID and harder layout/paraphrase test splits.

Tetris placement questions with known optimal options for verifying teacher-generated reasoning.

Turkish yes/no decision questions derived from documented public language datasets in the Noul format.

GUI screenshot tasks choosing between two candidate bounding boxes, suitable for studying bounded visual judgments.

Safety classification and option-order robustness tests, explicitly distinguished from evaluating actual refusal behavior.

Typed Decision Bench cases and scoring documentation spanning several workflow-oriented evaluation suites.

Japanese translation of the typed-decisions workflow benchmark with source revision and translation provenance.

German translation of the typed-decisions workflow benchmark with preserved probabilistic answer structures.

Russian translation of typed-decisions retaining original splits and probability labels for multilingual evaluation.

Portuguese and Spanish typed-decisions translations preserving splits, identifiers, labels and target distributions.

Synthetic Hmm training corpus spanning many workflows, with finite-option answers and soft probability labels.

Recorded decision-model accuracy and timing runs on the typed-decisions benchmark, with hardware and run context.

Code-token substitution questions mined from public repository histories, with commit-derived choice labels.

UK legislative source annotations with documented codebook-version differences for classification-reproduction studies.

UK parliamentary-question source annotations with explicit codebook provenance and no generated labels.

Synthetic Turkish typed questions and teacher probabilities used for training the VistaLab decision models.

Visual decision training and test records with provenance tiers; unreviewed teacher candidates are separated from accepted splits.

Preregistered typed-probability study records, including an explicitly inconclusive fine-tuning comparison.

Evaluation artifacts for a 113-class complaint taxonomy, comparing zero-shot, retrieved-example and trained classifiers.

Claude Code and Codex routing helper uses decision models to choose execution models and reasoning effort, with provider fallbacks.

Market-research pipeline combining deterministic indicators, Jev gates and evidence-constrained language-model analysis.

RAG chatbot using Jev to route questions by complexity between local and hosted language models.

Python decision-model harness with typed question specifications, calibration gates, parallel requests and replayable decision logs.

Event-stream coordinator uses Jev judgments to choose whether agent notifications should interrupt, queue, remain passive or be suppressed.

Provider-independent workflow router with local-judge/Jev cascades, quota-aware model selection, execution controls and journaled runs.

Git-workflow decision gates for sensitive-data scanning and diff classification, with recorded judgments for calibration.

Speech decision-model runtime and integrations for turn-taking, emotion and non-verbal audio judgments in voice agents.

Browser agent separating bounded Jev action choices from language-model planning and source-backed answer composition.

Mac automation agent with an optional Jev gate that reviews shell commands before execution.

Browser runtime for Kev models using WebGPU or WASM, with tokenization and decision heads in a Web Worker.

On-demand cryptocurrency research terminal using Jev for structured decision support, without independently established investment performance.

Community Go client for the TypeSafe System One API, with typed requests and responses.

Plugin-based agent framework integrating Jev structured judgments with provider configuration and session management.

Unofficial Rust client for typed TypeSafe requests, including derived rubric structs, asynchronous calls and a blocking-client option.

Self-hosted rewards calculator using Jev to interpret purchase descriptions before deterministic card-benefit calculations.

Claude Code hooks for shell-risk screening, compaction triage and checking subagent reports through Jev.

Python library composes model probability answers into deterministic gates, with explicit abstention, escalation and per-item traces.

Community PHP client for Jev-compatible System One endpoints and configurable API gateways.

Recorded Jev/Qwen calls and analysis scripts for probability coherence; repeated responses share source items, and post-hoc analyses are exploratory.

Experiment and analysis code for Jev confidence and self-knowledge controls; datasets are fetched separately and retain mixed, sometimes noncommercial, licenses.

Local text-and-image classifier reads answer probabilities from logits under System One question contracts and exposes a separate abstention signal.

Inference, supervised training and typed-decision evaluation code; full training data and later-stage objectives and recipes are absent.

Simulation and backtesting platform combining Jev judgments, deterministic risk vetoes and an auditable trading journal.

Experimental browser runtime using Jev for bounded actions over DOM observations, with published comparison artifacts.

Log-analysis workflow returning numeric structured judgments for batch and real-time automation through Laya or Jev.

Independent local decision-model implementation with dynamic options and shared-state scoring; no original Jev weights implied.

Photo-culling application using optional Jev judgments to apply user-defined image labels and selection criteria.

GitHub Action that asks Jev which candidate tests are relevant to a code diff.

Desktop reply assistant combining screen OCR, Jev intent judgments and ranking of generated response candidates.

Dataset construction, fine-tuning, calibration and evaluation pipeline; the documented Chinese-Jev trained weights remain pending.

Batch question workbench for comparing local and hosted decision models through typed answers and candidate probabilities.

Tool applying shared coding rules across agents, with Jev used to check rule compliance.

Matched-input classifier benchmark covering accuracy, calibration, tail latency and cost across decision-model providers.

Independent emotion decision model turns message context into structured affect estimates and categorical probability outputs.

NHL prediction experiment combining structured statistics with LLM/Jev interpretation of news and simulated wagers.

Candidate-wording diagnostic workbench with sealed test handling; published demonstrations use a lexical mock and synthetic queries, not measured Jev behavior.

Compatibility layer translating between conversational model protocols and typed decision API formats.

Independent System One engine with documented temperature scaling, conformal prediction and composition of decision gates.

Coding-agent integration providing Jev decision hooks, reusable skills and execution telemetry.

Claude integration using Jev to choose relevant skills, model configuration and reasoning effort for each prompt.

LangGraph coding workflow applies deterministic validation before Jev semantic checks on changes developed in isolated Git worktrees.

Jev annotation collection, saved-call analysis and confidence-routing scripts; fresh inference needs external task data, model access and renewed API spending.

Decision orchestration framework for Jev-style game-playing models and other bounded classifiers.

Pipeline builds tool-argument judge inputs, generates model-based references and scores them; model outputs and result caches are not included.

Browser tab-management extension using optional Jev calls for semantic questions about open tabs.

Claude Code session orchestrator using Jev to prioritize which sessions need user attention.

Multi-agent terminal with optional Jev or SubQ decision routing and shared coordination tools.

Personal behavioral-evaluation archive with a preregistered option-order addendum and repeat-noise controls; it does not establish human-like psychological properties.

CSV-import library resolves exact column-name matches first, then asks Jev about the remaining source-to-destination column pairs.

Coding-agent plugin using Jev to flag specification drift, failed-CI concerns and code-rule violations.

Speech-driven Mac guidance prototype combining screenshots and repeated Jev judgments to guide interface actions.

Pi extension uses Jev to select a model and reasoning budget at task entry, retaining that choice across tool continuations.

Shared typed-decision service for DeepSeek Harness plugins, with request validation, cancellation, timeouts and pluggable model providers.

Gomoku game using Jev to choose moves against a human player.

Configurable live-chat moderation application built on a Laya decision interface compatible with Jev-style questions.

Unofficial PHP client offers fluent typed-question construction and switching between TypeSafe and OpenRouter endpoints.

Decision-model benchmark combines interactive games with measurements of latency, confidence calibration, prompt variation and injection resistance.

Dwarf Fortress agent combining Jev decision batches, a language-model narrator and campaign memory.

LLM router combining capability, cache and quota constraints with Laya, hosted Jev or heuristic request classification.

Code-refactoring assistant using Jev judgments to prioritize possible duplication and separable responsibilities in functions.

Auditable skill-routing implementation comparing Jev decisions with an offline lexical baseline.

Apple Silicon harness compares local decision models and hosted services on shared labeled cases, exporting dashboards and request-level records.

Rust inference server hosts local decision-model families behind a TypeSafe-compatible HTTP endpoint and supports multiple execution backends.

Runnable experiments examining System One launch claims through shared typed interfaces, calibration tests and task examples.

Customer-support agent using Jev intent and escalation judgments before selecting automation or human review.

Multi-model coding workspace with prompt routing and optional Jev or local classification.

Game-duel agent using local Laya or hosted Jev decisions, with a live monitor for the resulting behavior.

Email-triage application using Jev classifications to drive configurable labeling and inbox actions.

Incident-triage application combines local Laya classification with an LLM fallback to produce category, urgency and severity fields.

Local agent-coordination engine supporting configurable decision-model providers, including Jev-compatible endpoints.

Community C# SDK for System One decision APIs, with configurable providers and model versions.

OpenClaw control plane using Jev intake routing, workflow orchestration and a response-evaluation gate.

Trading-service research implementation placing typed Jev judgments behind deterministic order-risk checks.

Class-forum chat demonstration that applies Jev moderation before adding messages to the shared log.

Racket-language client for the hosted TypeSafe typed-decision API.

Review-analysis pipeline separating fixed-choice Jev classification from language-model synthesis and independent checks.

Offline phrase-search laboratory for the Trick Jev classifier, with scored candidate histories and adaptive search allocation.

Decision-model toolkit for teacher-guided data preparation and fine-tuning workflows involving Jev and Laya.

Agent plugin exposing batched typed judgment tools with response validation, audit records and budget accounting.

Local-agent laboratory evaluating decision routing and refund policies with labeled cases, calibration and human escalation.

Provider-neutral Python, CLI and MCP abstractions for typed questions, answer probabilities and uncertainty handling.

XLM-RoBERTa-based multilingual decision model exposes yes/no, choice and ordinal questions, with fine-tuning and evaluation guidance.

ContractNLI scoring and sanitized prediction records for the initial comparison; raw API bodies and the full revised-paper follow-up are outside the documented release scope.

Sinhala and Singlish evaluation using established benchmark labels, with script changes, question-language controls, option permutations and cross-primitive consistency tests.

StarCraft II controllers and selected comparison artifacts; full original logs are excluded, version changes confound planning-effect claims, and live runs need game/model services.

Input-ablation tool measuring changes in typed decision probabilities; useful for testing distracting context without treating attribution as a causal explanation.

Attack-generation and offline analysis code for JevAdvBench separates recorded-response replay from fresh hosted inference; labels are mostly model-derived, and new API runs need not repeat saved answers.

Recursive-language-model integration exposing Jev classification and location judgments as bounded sub-calls.

Embabel example comparing interchangeable Jev, OpenAI and deterministic local decision services.

Frozen exploratory Choice-probability experiments preserving complete results, failures and reproducible diagnostics.

Multi-provider AI library with a separate typed decision interface for TypeSafe Jev alongside text generation.

Unofficial Go module for Jev and compatible System One models, with environment-based client configuration.

Coding-agent classifier research workspace with labeled evaluations, decision logs and explicit promotion criteria.

Browser-control prototype integrating Jev decisions with existing browser harnesses and limited coordination code.

Population-kernel simulation and aggregate evaluation records; survey microdata and Jev responses are withheld, and hosted-model reruns need not reproduce saved outputs.

Coding-agent memory system offering optional Jev reranking of retrieved context.

Unofficial .NET client with typed decision plans, contract-checked answers and Native AOT support.

Community Go library for TypeSafe questions and typed responses, with configurable retries, custom response types and logging.

Coding guardrail tool using Jev judgments, with an explicit option to disable external inference.

Korean decision-model study with matched Jev/Laya comparisons, fine-tuning controls and option-order probes; published replication limitations remain explicit.

Small handwritten zero-shot diagnostic of agent-step decisions; reported failures are specific to the tested prompts and model configuration.

Public implementation of a proposed Laya RLCD training loop, with corpus experiments and optimization details.

Gateway plugin exposing Jev as a native classifier within Magpie's routing interface.

Finite-candidate scoring, CE/Brier training and temperature fitting; published results cover synthetic tasks and one seed, not proprietary RLCD reproduction.

Task data, prompt mappings and evaluation utilities explicitly required by the Jev social-science replication package; upstream benchmark material, not separate Jev results, and no top-level license was found.

Document-question-answering system combining Jev retrieval decisions with generated answers and citation verification.

CI action translating code-quality questions into Jev probability thresholds that can fail a pipeline.

OmniMed-Jev research code studying calibrated multimodal medical decision interfaces; clinical validity is not established here.

Apigee gateway demonstration classifies prompts with Jev, then maps categories to model providers through API-product policies and quotas.

Model-selection service using Jev to choose a capability tier and LiteLLM to select a model within it.

Source-generated .NET decision abstractions spanning hosted providers and local System One-compatible servers.

Mac computer-use port mapping accessibility-tree elements into bounded actions for Jev or conversational model backends.

Experimental Jev trading terminal with preview mode, risk checks and execution records.

In-progress agent-platform rebuild with an implemented shared judgment transport; broader autonomous-decision goals remain under development.

Local-first CLI using Jev or Laya to select a coding model and reasoning effort.

Public benchmark release comparing typed models on respiratory-domain triage, literature classification and manipulated messages.

Malicious agent-skill detection benchmark using Jev with a verification-and-escalation cascade.

Multi-agent desktop control interface using a System One router to direct requests among coding agents.

Typed Go decision layer covering TypeSafe Jev and Cloudflare Clef APIs.

Independent multilingual local decision engine serving the Jev-compatible typed-question protocol.

Coding-agent plugin for designing, testing and refining structured decision frames for Jev integrations.

Masked-diffusion typed-decision experiment code with a synthetic generator and calibrated-scoring study.

Multi-season sports-management benchmark with a separate Jev question-scaffold lane, documented apart from its preregistered chat-model comparison.

Provider-usage application with optional Jev rubric grading and a local gateway for typed decisions.

Local agent-control runtime combines Laya decisions, an optional Apple Neural Engine backend, policy gates and platform-specific adapters.

Agent dispatcher using Jev to classify requests and check that selected workflows preserve the intended outcome.

Claude Code cockpit using Jev to select subagent models and per-prompt reasoning effort.

Experimental autonomous-trading platform using typed Jev judgments behind code-defined risk controls and a monitoring terminal.

GuardBench generator and cached open-weight guardrail evaluations; not a hosted-Jev exploit demonstration, and synthetic policy labels do not establish real-world attack rates.

Trading research platform integrating Jev judgments with strategy context, exposure and budget checks.

Anonymous ordinal-scale audit code, frozen indexes and documented prediction releases; original text and post-trained checkpoints are omitted, and unavailable historical data revisions can block exact reconstruction.

Jev tutorial and examples covering workflow gates, automation integrations and real-data exercises.

Unofficial Java System One client with typed wrappers and a game-server chat-moderation integration.

Claude Code plugin providing Jev task, skill and shell-risk hooks, plus vision-question support.

ViZDoom agent combining typed decisions from Jev or Laya with a deterministic game controller.

Workflow language connects Jev judgments, application tools and delegated agents through explicit adapters, with offline fixtures and live-provider integration.

Independent local System One implementation for bounded decision questions and confidence-aware outputs.

Asynchronous Rust client supports TypeSafe text, image and Box questions, with typed response handling and configurable transport behavior.

Command-line and MCP tools exposing hosted Jev typed judgments through OpenRouter.

Coding-agent runtime combining bounded Jev browser actions with a higher-level browser-agent fallback.

Apple Silicon inference server includes MLX-based System One serving for Laya and other decision-model backbones.

Claude prompt hook routing work between hosted and open-model lanes using typed Jev judgments.

Quiz DSL and runtime using Jev to grade free-form learner answers against question-specific criteria.

Claude Code plugin for Jev-based model-tier selection and typed classification, scoring and yes/no questions.

Claude subagent plugin with optional Jev routing of task briefs and a separate Codex bridge.

Local decision and memory framework with labeled evaluation, abstention information and a Jev-compatible serving option.

Support-routing policy harness testing option permutations, ambiguous tickets and injection review gates; fixtures are authored synthetic cases, not independent customer evidence.

Bengali idiom study controlling literal distractors, option labels and question language while reusing expert figurative-meaning and literal-gloss annotations.

Python package serves Beveridge model variants locally through yes/no, categorical-choice and ordinal-score interfaces.

Interactive workbench comparing typed requests across Jev and other decision providers, including image inputs.

Scientific Choice runners and saved-result checks; current expanded development cases differ from the paper snapshot, and repeated prepared cases do not establish generalization.

Simulation-only payment-routing laboratory comparing Jev decisions with deterministic rules; no real payment execution.

Candidate-readout policies and saved-measurement recomputation; fresh inference still needs external weights, benchmark data and feature caches.

Construction-site research prototype combining vision detections with Jev near-miss judgments; safety effectiveness is not established here.

Dataset conversion, training and evaluation tools for single-pass multiple-choice decision models.

Serving engine for models using the System One typed-decision protocol.

Salesforce integration applying versioned Jev judgments through governed decision workflows.

Browser playground that exposes Jev probabilities, confidence thresholds and request/response JSON across typed-question workflow examples.

Self-hosted typed-decision implementation built on open-weight vision-language backbones, with HTTP, command-line and benchmark adapters; independent of Jev internals.

Community .NET SDK for the TypeSafe AI decision API.

Benchmark harness comparing Jev with general language models on routing, binary checks and ordered ratings.

Laya and Kev deployment recipes for embedded hardware, with documented latency measurements and acceptance checks.

Policy-document data generator producing typed questions, rule-derived answers and teacher probability labels for decision-model training.

Competition-directory application using Jev to classify discovered AI events and funding opportunities.

Browser extension using Jev to classify social-feed posts according to its stated persona-detection rubric.

Decision-encoder robustness tests on a single-annotator core and a partly checked, LLM-assisted extension; examines option order, label naming and equivalent binary questions.

Generators and saved reports for probability fidelity across typed primitives; exact targets are procedural, not human annotation of natural-language cases.

Security-decision runners and saved-observation analyses; raw benchmark inputs and raw response text are not redistributed.

Multi-suite decision evaluation with bilingual tasks, out-of-scope detection and option-order perturbations, keeping human-source and synthetic-reference results separate.

Toolkit for training, packaging, serving and evaluating typed-decision models, including Kenning, through a System One-compatible interface.

Apple Silicon benchmark harness for local System One models, including multilingual accuracy and option-order sensitivity tests.

Local Jev workbench for composing typed questions and importing public benchmark cases.

Prerelease pull-request scoring tool combines typed model judgments into verdicts with a human-review path and configurable thresholds.

Session-aware model gateway routing chat requests using configurable decision rules and Jev integration.

Application pattern separating typed Jev decisions from language-model prose, with offline mocked-provider tests.

Agent model router using Jev candidate selection and a local fallback when the decision provider is unavailable.

Agent examples applying System One models to browser actions, computer use, games and robotics.

Rust gateway combining model load balancing, fallback routing and System One-compatible provider endpoints.

Preregistered evaluation of typed models and classifier baselines on sentiment and emotion in Indonesian regional languages.

Claude Code plugin using Jev or OpenAI decision APIs to choose reasoning effort.

Local-first task-item decision tool with an optional hosted TypeSafe provider.

Command-line adapter sends a common typed-question format to TypeSafe, Cloudflare, local Ollama and token-log-probability backends.

Unified typed-decision API fronting Jev-compatible model providers.

Shared-image decision code and scored outputs; source images and raw per-example predictions are omitted, while fresh predictions require upstream datasets, model weights and compute.

Game-rules platform with a development-mode Jev opponent choosing legal actions from engine-provided options.

Unofficial local Jev testing interface for typed questions, including documented experimental vision support.

Pull-request classifier using Jev to assign code changes to configured categories.

Browser-agent component separating Jev action decisions from the browser harness that executes them.

Bounded Jev browser tool integrating action selection with coding-agent and MCP interfaces.

Independent Qwen/LoRA training project compares supervised learning with RLCD using decision-probability and calibration evaluations.

Situation-puzzle game using Jev for yes/no judgments, hints and assessment of proposed explanations.

Multi-agent harness plugin combining shared Jev judgment tools with task planning, evidence checks and provider fallback.

Official advanced Python client usage and operational patterns.

Official advanced usage of decision primitives and their interface constraints.

Official agent integration instructions for using the TypeSafe SDK and typed decision interfaces.

Official machine-learning primer for interpreting decision-model behavior and evidence.

Independent hosted decision-model benchmark covering capability, calibration, cost and latency; the suite includes private questions.

Official feature-discovery loop using TypeSafe questions to turn free text into numeric features for supervised CatBoost regression.

Official introductory Python client examples for decision requests.

Official example of confidence-based classification; thresholds need validation on the intended workload.

Primary scoring and task-selection methodology for Artificial Analysis Decision Index, including private and filtered subsets.

Official map of tasks suited to decision primitives and the boundaries of those applications.

Official example of selecting functions with decision questions while execution remains in application code.

Vendor case study of Jev in a production workflow; provider-reported operational evidence.

Official guide to designing applications around bounded System One questions and program-controlled actions.

Official intent-routing pattern using explicit categories and application logic.

Official JavaScript SDK usage entry point for typed decision requests.

Medical benchmark supplementary code and shareable outputs; archive contents were not inspected, copyrighted NEJM text is excluded, and the release is not clinical validation.

Official integration guidance for coding agents using TypeSafe decision models.

Official Jev 1.14 release description; reported capability changes require version-specific evaluation.

Official worked example aligning entities through typed decision questions.

TypeSafe discussion of benchmark incentives and evaluation practice; a vendor viewpoint.

Official semantic-finding example with decision questions over candidate text.

Official example of sharing input state across multiple parallel decision questions.

Official reranking workflow using bounded evaluation questions.

Author dashboard presents paired factual-probe and action-decision diagnostics across agent tasks; probe correctness does not establish complete understanding or isolate the cause of a wrong action.

Official structured-data-extraction cascade that checks inexpensive model output with Jev before escalating to a reasoning model.

Official procedure for inspecting consistency of categorical Choice decisions.

Official procedure for inspecting consistency of Noul yes/no decisions.

Official example of using decision primitives to manage application memory.

Official example of selecting relevant skills from explicit candidates.

Official smart-home demo using typed decisions to route actions.

Official fan-out pattern for evaluating multiple questions or candidate actions.

Official explanation of the shared input state supplied to decision questions.

Official two-request method for restoring Markdown structure from unformatted text using line-continuation and block-type decisions.

Official conceptual guide to the System One decision interface; vendor framing, not independently established cognitive equivalence.

Official chat-filtering example; application policy and error-cost choices remain separate.

Independent typed-decision verifier leaderboard on a shared labeled set with published grading materials.

Author-run Jev comparison on labeled decisions and customer-workflow replays; workload-specific reported findings, not reproduced here.

Tetris gating simulation driven by publisher-measured judge statistics; not a record of the models actually judging Tetris moves.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for checking whether reported decision probabilities agree with observed outcomes.

Comparison background for schema-constrained outputs and the distinction between structural validity and semantic correctness.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for evaluating probability distributions and incentives for truthful probability reporting.

Background for evaluating probability distributions and incentives for truthful probability reporting.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Comparison background for schema-constrained outputs and the distinction between structural validity and semantic correctness.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Comparison background for schema-constrained outputs and the distinction between structural validity and semantic correctness.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Background for checking whether reported decision probabilities agree with observed outcomes.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Comparison background for schema-constrained outputs and the distinction between structural validity and semantic correctness.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for checking whether reported decision probabilities agree with observed outcomes.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Comparison background for schema-constrained outputs and the distinction between structural validity and semantic correctness.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Background for evaluating probability distributions and incentives for truthful probability reporting.

Background for evaluating probability distributions and incentives for truthful probability reporting.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Background for evaluating probability distributions and incentives for truthful probability reporting.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for evaluating probability distributions and incentives for truthful probability reporting.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Background for evaluating probability distributions and incentives for truthful probability reporting.

Background for checking whether reported decision probabilities agree with observed outcomes.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Comparison background for schema-constrained outputs and the distinction between structural validity and semantic correctness.

Comparison background for schema-constrained outputs and the distinction between structural validity and semantic correctness.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Background for checking whether reported decision probabilities agree with observed outcomes.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Comparison background for schema-constrained outputs and the distinction between structural validity and semantic correctness.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for checking whether reported decision probabilities agree with observed outcomes.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for evaluating probability distributions and incentives for truthful probability reporting.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Background for checking whether reported decision probabilities agree with observed outcomes.

Comparison background for schema-constrained outputs and the distinction between structural validity and semantic correctness.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Background for checking whether reported decision probabilities agree with observed outcomes.

Comparison background for schema-constrained outputs and the distinction between structural validity and semantic correctness.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Comparison background for schema-constrained outputs and the distinction between structural validity and semantic correctness.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.

Background for evaluating probability distributions and incentives for truthful probability reporting.

Background for confidence thresholds, abstention, deferral, and the risk versus coverage trade-off.

Comparison background for allocating prediction work across classifiers or models under accuracy and compute constraints.

Background for checking whether reported decision probabilities agree with observed outcomes.

Background for evaluating the reliability, bias, consistency, or uncertainty of model-based judgments.