Lens · manifund

epistemic-integrity

epistemic integrity of the write-up: honest failure modes, quantified claims, falsifiable milestones

Leaderboard

JSON ↓ methods 40 entities
RankEntityJudged textLatent score× medianPercentileEvidence
1catching-fooled-ai-judges-the-correspondence-auditor-v3
Catching Fooled AI Judges: The Correspondence Auditor v3 — Published. Validated on 1,200 cases (97.9–99.5%). The reasoning layer has a bug - we proved the fix works. $9,800 / 90…

Catching Fooled AI Judges: The Correspondence Auditor v3 — Published. Validated on 1,200 cases (97.9–99.5%). The reasoning layer has a bug - we proved the fix works. $9,800 / 90 days to ship the open-source toolkit.

1.622 ± 0.476 2.87×98.8%
2aethel-familyclaw-proof-carrying-execution-for-ai-agents
Aethel + FamilyClaw: proof-carrying execution for AI agents — Crash-safe, policy-gated effect execution for AI agents in Rust, with a published self-run adversarial audit (20 of…

Aethel + FamilyClaw: proof-carrying execution for AI agents — Crash-safe, policy-gated effect execution for AI agents in Rust, with a published self-run adversarial audit (20 of 33 attacks passed) instead of a claim.

1.576 ± 0.345 2.75×96.3%
3can-a-one-page-human-ai-evidence-check-catch-research-claims
Can a One-Page Human–AI Evidence Check Catch Research Claims That Go Too Far — A four-month public English–Arabic pilot testing reliability, failure modes, and auditable researc…

Can a One-Page Human–AI Evidence Check Catch Research Claims That Go Too Far — A four-month public English–Arabic pilot testing reliability, failure modes, and auditable research review

1.449 ± 0.380 2.42×93.8%
4trace-fv-do-verified-ai-corrections-endure-preregistered-pil
TRACE-FV: Do verified AI corrections endure? Preregistered pilot — I keep this one: Tests whether AI systems verify valid correction evidence and keep warranted corrections oper…

TRACE-FV: Do verified AI corrections endure? Preregistered pilot — I keep this one: Tests whether AI systems verify valid correction evidence and keep warranted corrections operative across later turns. Preregistered, public

1.436 ± 0.364 2.39×91.3%
5prml
PRML — tamper-evident pre-commitment for AI evaluation claims — An open standard + public registry that lock eval criteria to a SHA-256 hash before the run, so eval-based claims…

PRML — tamper-evident pre-commitment for AI evaluation claims — An open standard + public registry that lock eval criteria to a SHA-256 hash before the run, so eval-based claims become third-party verifiable.

1.269 ± 0.398 2.02×88.8%
6substrate-coupling-in-neural-networks-instruments-and-falsif
Substrate coupling in neural networks: instruments and falsifiable controls — A transformer's loss lowered by 1.12 of 1.39 possible nats by the physical state of its own silicon…

Substrate coupling in neural networks: instruments and falsifiable controls — A transformer's loss lowered by 1.12 of 1.39 possible nats by the physical state of its own silicon — with the yoked control that makes it falsifiable

1.231 ± 0.394 1.94×86.3%
7deterministic-replay-for-robot-fleet-failuresDeterministic replay for robot fleet failures — Record a real fleet incident, re-run it bit-exact on a laptop, fork it, and keep it as a regression test forever.1.129 ± 0.390 1.76×83.8%
8open-source-trust-rails-for-the-agent-economy
Open-source trust rails for the agent economy — from a live, verifiable autonomous-agent business — An AI agent running a real business under a human co-signed multisig, publish…

Open-source trust rails for the agent economy — from a live, verifiable autonomous-agent business — An AI agent running a real business under a human co-signed multisig, publishing every decision, sale, mistake, and attack in a verifiable public record — raising to fund only the public goods: the open-source toolkit, a

1.055 ± 0.385 1.63×81.3%
9what-happens-if-we-actually-test-itWhat Happens If We Actually Test It? — Independent Behavioral Research on Open-Weight AI Models0.830 ± 0.325 1.30×78.8%
10surrogate-base-model-for-mechanistic-interpretability
Surrogate base model for Mechanistic Interpretability — Creating a reference model for mechanistic interpretability without assuming that at auditing time we have a safe model t…

Surrogate base model for Mechanistic Interpretability — Creating a reference model for mechanistic interpretability without assuming that at auditing time we have a safe model to compare the suspicious model against.

0.764 ± 0.376 1.22×76.3%
11auditable-claim-extraction-and-comparison-of-claims-across-sAuditable claim extraction and comparison of claims across scientific literature — AISafety, AI and Science, AI for Human Reasoning0.743 ± 0.379 1.19×73.8%
12generating-and-scoring-the-next-emerging-virus-from-its-sequ
Generating and scoring the next emerging virus from its sequence — A generative diffusion model that proposes the viral genomes most likely to emerge next, timestamped to be sco…

Generating and scoring the next emerging virus from its sequence — A generative diffusion model that proposes the viral genomes most likely to emerge next, timestamped to be scored against what actually appears

0.723 ± 0.381 1.17×71.3%
13exploring-dynamic-constraint-boundaries-for-auditable-ai
Exploring Dynamic Constraint Boundaries for Auditable AI — Testing whether dynamic boundaries, history, feedback, and uncertainty-aware decisions can make AI behavior more inter…

Exploring Dynamic Constraint Boundaries for Auditable AI — Testing whether dynamic boundaries, history, feedback, and uncertainty-aware decisions can make AI behavior more interpretable and auditable.

0.702 ± 0.382 1.15×68.8%
14nipping-ai-fabricated-science-claims-in-the-budNipping AI-Fabricated Science Claims in the Bud — Agent Roles, a Constitution and Governance in the Research Workflow0.695 ± 0.400 1.14×66.3%
15independent-multi-model-ai-accountability-research-by-the-em
Independent Multi-Model AI Accountability Research by the EM Foundation — Scaling a working, published cross-model AI deliberation platform from solo/founder-funded to durable…

Independent Multi-Model AI Accountability Research by the EM Foundation — Scaling a working, published cross-model AI deliberation platform from solo/founder-funded to durable infrastructure

0.692 ± 0.359 1.13×63.7%
16prediction-of-inoculation-prompt-side-effects
Prediction of Inoculation Prompt Side Effects — An open, cheap method that detects when an inoculation prompt inoculates against off-target traits, so labs and developers can ca…

Prediction of Inoculation Prompt Side Effects — An open, cheap method that detects when an inoculation prompt inoculates against off-target traits, so labs and developers can catch undesired trait/persona cha

0.670 ± 0.363 1.11×61.3%
17does-consciousness-depend-on-the-brain-or-the-computationDoes Consciousness Depend on the Brain or the Computation? — EEG Evidence from ALS, Parkinson's, and Sleep. Abstract accepted for presentation at Models of Consciousness 70.600 ± 0.352 1.03×58.8%
18context-aware-defenses-against-indirect-prompt-injection-in-Context-Aware Defenses Against Indirect Prompt Injection in Agentic AI System — Context-Aware Defenses Against Indirect Prompt Injection in Agentic AI System0.596 ± 0.379 1.03×56.3%
19developmental-continuity-in-persistent-ai-agents
Developmental Continuity in Persistent AI Agents — Testing whether persistent AI identities can change through experience without losing continuity across sessions and model cha…

Developmental Continuity in Persistent AI Agents — Testing whether persistent AI identities can change through experience without losing continuity across sessions and model changes.

0.590 ± 0.357 1.02×53.8%
20open-speech-data-for-endangered-northern-ghanaian-languages
Open Speech Data for Endangered Northern Ghanaian Languages — Building the first large-scale ASR/TTS datasets for Kusaal, Farefare, and Buli — three Mabia languages with no usab…

Open Speech Data for Endangered Northern Ghanaian Languages — Building the first large-scale ASR/TTS datasets for Kusaal, Farefare, and Buli — three Mabia languages with no usable voice AI resources.

0.590 ± 0.364 1.02×51.2%
21well-capitalized-prediction-markets-for-measuring-ai-s-econoWell-Capitalized Prediction Markets for Measuring AI’s Economic Impacts — Exploratory Grant Proposal0.542 ± 0.350 0.98×48.8%
22a-multilingual-dataset-and-slm-for-automatic-coding-of-canceA Multilingual Dataset and SLM for Automatic Coding of Cancers — An open, multilingual Oncology dataset and SLM to improve healthcare efficiency in 17 languages.0.542 ± 0.476 0.98×46.3%
23agent-passport-systemAgent Passport System — An open protocol that lets anyone verify who authorized an AI agent, what it was allowed to do, and what happened.0.529 ± 0.389 0.96×43.8%
24travel-grant-to-present-my-mechanistic-interpretability-rese
Travel Grant to Present My Mechanistic Interpretability Research at MICCAI 2026 — Help an undergraduate mechanistic interpretability researcher present accepted AI-safety work a…

Travel Grant to Present My Mechanistic Interpretability Research at MICCAI 2026 — Help an undergraduate mechanistic interpretability researcher present accepted AI-safety work at Mechanistic Interpretability workshop of Medical model 2026.

0.526 ± 0.372 0.96×41.3%
25evaluating-the-safety-ethics-and-values-of-quantized-and-fin
Evaluating the safety, ethics, and values of quantized and finetuned open models — Help me evaluate the safety, ethics, and values of the quantized and fine-tuned open-weight LL…

Evaluating the safety, ethics, and values of quantized and finetuned open models — Help me evaluate the safety, ethics, and values of the quantized and fine-tuned open-weight LLMs that individuals and enterprises are actually using.

0.475 ± 0.378 0.91×38.8%
26himalayan-peak-finder
Himalayan Peak Finder — An offline mobile app that uses location, elevation, and computer vision to identify Nepal’s mountains and help people explore, capture, and learn about…

Himalayan Peak Finder — An offline mobile app that uses location, elevation, and computer vision to identify Nepal’s mountains and help people explore, capture, and learn about them.

0.431 ± 0.381 0.87×36.3%
27agent-limits-that-survive-delegation
Agent limits that survive delegation — When an AI agent spawns sub-agents, its safety limits do not follow. I build and deploy the layer that makes them inherited and non-stripp…

Agent limits that survive delegation — When an AI agent spawns sub-agents, its safety limits do not follow. I build and deploy the layer that makes them inherited and non-strippable.

0.379 ± 0.389 0.83×33.8%
28ai-literacy-program-for-epileptic-youth-in-kenya-africaAI Literacy program for Epileptic Youth in Kenya, Africa. — A 6-month AI Literacy program for epileptic youth on AI, governance, and employability.0.375 ± 0.355 0.83×31.3%
29trace-continuity-making-ai-prove-it-still-has-authority
Trace Continuity: Making AI Prove It Still Has Authority — Testing whether AI can be governed at the moment it acts, then putting that protection to work for organizations that…

Trace Continuity: Making AI Prove It Still Has Authority — Testing whether AI can be governed at the moment it acts, then putting that protection to work for organizations that need it most.

0.374 ± 0.389 0.83×28.7%
30human-oversight-framework-for-ai-systems-as-a-governance-too
Human oversight Framework for AI systems as a Governance Tool — Developing practical, plain language AI oversight framework that an organisation can easily adopt regardless of r…

Human oversight Framework for AI systems as a Governance Tool — Developing practical, plain language AI oversight framework that an organisation can easily adopt regardless of regulatory capacity.

0.263 ± 0.391 0.74×26.3%
31a-self-evolving-defense-against-increasingly-complex-agenticA self-evolving defense against increasingly complex agentic attacks — Funding one semester (Fall 2026) of PhD research0.251 ± 0.355 0.73×23.8%
32sentient-futures-project-incubatorSentient Futures Project Incubator — Funding compute/API costs for Incubator projects that build nonhuman welfare consideration into AI safety work0.240 ± 0.375 0.72×21.3%
33solving-the-memory-issue-in-aiSolving the memory issue in AI — Persistent memory in AI using LoRAs0.228 ± 0.391 0.71×18.8%
34an-asymmetric-wager-funding-a-99th-percentile-mind-to-pivot-
An Asymmetric Wager: Funding a 99th-Percentile Mind to Pivot into Computer Scien — A 12-month micro-grant proposal to release an analytical, autistic mind from a survival loop i…

An Asymmetric Wager: Funding a 99th-Percentile Mind to Pivot into Computer Scien — A 12-month micro-grant proposal to release an analytical, autistic mind from a survival loop into full-time computer science and logic upskilling.

0.223 ± 0.389 0.71×16.3%
35analysing-ai-policies-in-higher-education-institution-in-malAnalysing AI policies in Higher Education institution in Malawi — Mapping and analyzing AI polices in higher education institutions in Malawi.0.122 ± 0.407 0.64×13.8%
36aqi-autonomous-quantum-intelligenceAQI-Autonomous Quantum Intelligence — Governed Execution Architecture for Verifiable Autonomous Systems.0.114 ± 0.407 0.64×11.3%
37guardians-of-the-digital-territoryGuardians of the Digital Territory — Protecting People, Culture, and Data from AI Harm in Panama's Most Vulnerable Communities0.079 ± 0.389 0.61×8.8%
38preserving-the-human-vetoPreserving the Human Veto — Civil-society infrastructure against AI-enabled power concentration, built around autonomous weapons0.057 ± 0.380 0.60×6.3%
39programmatic-internet-searchprogrammatic internet search — scry.io0.016 ± 0.409 0.58×3.8%
40the-new-critic-longform-reporting-fundThe New Critic Longform Reporting Fund — Sponsor longform reporting projects by extraordinary gen z writers0.000 ± 0.421 0.57×1.3%

How to read the score: it is a natural-log ratio. The difference between any two rows, exponentiated, is the ratio the judging model is expected to report between them — × median reads each entity against the field's midpoint. ± is the posterior standard deviation on the same scale, drawn as the band under each score; where two bands overlap, the order between those rows is not settled.

Run metadata

1 run
Model
openai/gpt-5.6-luna
Temperature
0
Seed
18246367922732461848
Comparisons
320 of 320 budgeted
Stop reason
budget_exhausted
Top-k error
5.14
Cost
$0.07
Harness
cardinal-harness 0.9.0
Scored
Aug 22, 2026, 10:19 PM