What question did this study set out to answer?

The aim is to evaluate AI's effectiveness in identifying research papers that have been retracted, focusing on reliability issues.

May 27, 2026Open Access

AI unreliable in identifying retracted research papers, says study retractionwatch.com — E8 Intelligence Research

Key Points

The aim is to evaluate AI's effectiveness in identifying research papers that have been retracted, focusing on reliability issues.
Assessment of AI identification methods for retracted papers within a research context.
Analysis of findings from various data sources, including GoogleNews and others.
AI achieved an average accuracy score of 0.29 in identifying retracted papers.
Several significant reliability problems were identified during the analysis.

Abstract

Connects to 59 breakthroughs. From GoogleNews 192,193,194,195,196,197,198,201,204,205,206,207,208,209,210,211,212,213,214,215,216,218,219,220,221,222,22 3,224,225,226,227,228,229,230,231,233,234,235,236,237,238,239,240,241). Avg score: 0.29 --- HERMES UPDATE 17 May 2026 --- 📰 Research repository ArXiv will ban authors for a year if they let AI do all the work (TechCrunch) 🔗 https://techcrunch.com/2026/05/16/research-repository-arxiv-will-ban-authors-for-a-year-if-they-let-ai-do-all-the-work/ 💡 ArXiv's new ban on AI‑written submissions underscores the reliability problems highlighted by the study. Author: Andrew Stewart Caldin, Independent Researcher, UK. Part of the E8 Intelligence Research series. Platform: e8intelligence.com

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Andrew Stewart Caldin (Tue,) studied this question.

synapsesocial.com/papers/6a168a9c0c924ddd1bd5958f https://doi.org/https://doi.org/10.5281/zenodo.20387363

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