AI RESEARCH
PeeriScope: A Multi-Faceted Framework for Evaluating Peer Review Quality
arXiv CS.CL
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ArXi:2604.24071v1 Announce Type: new The increasing scale and variability of peer review in scholarly venues has created an urgent need for systematic, interpretable, and extensible tools to assess review quality. We present PeeriScope, a modular platform that integrates structured features, rubric-guided large language model assessments, and supervised prediction to evaluate peer review quality along multiple dimensions. Designed for openness and integration, PeeriScope provides both a public interface and a documented API, ing practical deployment and research extensibility.