arXiv (All)
open access
Predictive Credit: Measuring What Scientific Explanations Add to Experimental Forecasts
Research agents explain planned experiments. We measure predictive credit with paired forecasts sharing an intervention, forecaster, and outcome while varying description, matched explanation, and donor context. Five checks track commitment, delivery, predictive gain, alignment, and known-signal upt
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Scientific Explanation and Moral Explanation#747906
- SCIENTIFIC INCENTIVES#2037
- Measuring the predictability of life outcomes with a scientific mass collaboration#613540
- The Causal Economy Approach to Scientific Explanation#734822
- How Proper Scoring Rules Shape LLM Forecasting#997535
Record · ID 1154937
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive