Lens · manifund-goals

importance-for-ai-safety-technical

importance of this evaluation criterion to a grantmaker whose aim is advancing technical AI safety research

Leaderboard

JSON ↓ methods 4 entities
RankEntityJudged textLatent scorePercentile
1theory-of-change-plausibility
Plausibility of the causal path from activities to claimed impact — whether the mechanism connecting what the team will do to the outcome they promise survives scrutiny step by…

Plausibility of the causal path from activities to claimed impact — whether the mechanism connecting what the team will do to the outcome they promise survives scrutiny step by step.

0.487 ± 0.34787.5%
2impact-per-marginal-dollar
Expected impact per marginal dollar at the stated ask — how much good the next dollar of funding actually buys, given the project size, cost structure, and counterfactual fundin…

Expected impact per marginal dollar at the stated ask — how much good the next dollar of funding actually buys, given the project size, cost structure, and counterfactual funding landscape.

0.021 ± 0.42662.5%
3team-track-record-evidenceVerifiable track-record evidence the team can execute — concrete, checkable prior work demonstrating the team has shipped comparable things before.0.018 ± 0.34637.5%
4epistemic-integrityEpistemic integrity of the write-up — honest failure modes, quantified claims, falsifiable milestones; whether the proposal reasons transparently rather than selling.0.000 ± 0.42612.5%

Run metadata

1 run
Model
anthropic/claude-haiku-4.5
Comparisons
32
Stop reason
budget_exhausted
Scored
Aug 20, 2026, 3:38 AM