PeeriScope: A Multi-Faceted Framework for Evaluating Peer Review Quality
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arXiv
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| Hauptverfasser: | , , , , , , , , |
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| Format: | Preprint |
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2026
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| author | Ebrahimi, Sajad Sadeghian, Soroush Ghorbanpour, Ali Arabzadeh, Negar Salamat, Sara Hosseini, Seyed Mohammad Le, Hai Son Bashari, Mahdi Bagheri, Ebrahim |
| author_facet | Ebrahimi, Sajad Sadeghian, Soroush Ghorbanpour, Ali Arabzadeh, Negar Salamat, Sara Hosseini, Seyed Mohammad Le, Hai Son Bashari, Mahdi Bagheri, Ebrahim |
| contents | 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, supporting practical deployment and research extensibility. The demonstration illustrates its use for reviewer self-assessment, editorial triage, and large-scale auditing, and it enables the continued development of quality evaluation methods within scientific peer review. PeeriScope is available both as a live demo at https://app.reviewer.ly/app/peeriscope and via API services at https://github.com/Reviewerly-Inc/Peeriscope. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_24071 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | PeeriScope: A Multi-Faceted Framework for Evaluating Peer Review Quality Ebrahimi, Sajad Sadeghian, Soroush Ghorbanpour, Ali Arabzadeh, Negar Salamat, Sara Hosseini, Seyed Mohammad Le, Hai Son Bashari, Mahdi Bagheri, Ebrahim Computation and Language 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, supporting practical deployment and research extensibility. The demonstration illustrates its use for reviewer self-assessment, editorial triage, and large-scale auditing, and it enables the continued development of quality evaluation methods within scientific peer review. PeeriScope is available both as a live demo at https://app.reviewer.ly/app/peeriscope and via API services at https://github.com/Reviewerly-Inc/Peeriscope. |
| title | PeeriScope: A Multi-Faceted Framework for Evaluating Peer Review Quality |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2604.24071 |