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Peer Prediction for Peer Review: Designing a Marketplace for Ideas

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arxiv 2303.16855 v1 pith:JGAQVMFY submitted 2023-03-29 cs.DL cs.SIecon.GNphysics.soc-phq-fin.EC

Peer Prediction for Peer Review: Designing a Marketplace for Ideas

classification cs.DL cs.SIecon.GNphysics.soc-phq-fin.EC
keywords peerreviewresearchideasplatformpredictionacademicaccurate
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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The paper describes a potential platform to facilitate academic peer review with emphasis on early-stage research. This platform aims to make peer review more accurate and timely by rewarding reviewers on the basis of peer prediction algorithms. The algorithm uses a variation of Peer Truth Serum for Crowdsourcing (Radanovic et al., 2016) with human raters competing against a machine learning benchmark. We explain how our approach addresses two large productive inefficiencies in science: mismatch between research questions and publication bias. Better peer review for early research creates additional incentives for sharing it, which simplifies matching ideas to teams and makes negative results and p-hacking more visible.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. AgentReview: Exploring Peer Review Dynamics with LLM Agents

    cs.CL 2024-06 unverdicted novelty 8.0

    AgentReview is the first LLM-based simulation framework for peer review that quantifies a 37.1% decision variation attributable to reviewer biases.