SynthesisFrontiers in research metrics and analytics2025
Artificial intelligence in the retraction spotlight: trends, causes and consequences of withdrawn AI literature through a systematic bibliometric review.
Synthesis in Frontiers in research metrics and analytics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: The rapid integration of artificial intelligence (AI) in scientific research has introduced new challenges to academic integrity, with increasing concerns about AI-related article retractions. This study conducts a comprehensive bibliometric analysis of retracted AI-related articles to characterize their prevalence, causes, and impact on scholarly communication. Methods: A systematic search was performed in Scopus using the terms "Artificial Intelligence" OR "AI" AND "retract Results: From an initial yield of 1,152 articles, 335 retracted publications met inclusion criteria after duplicate removal and screening. The analysis revealed that 46.3% (155/335) of retractions occurred in 2023, with a median retraction time of 550 days post-publication. Engineering accounted for 30.4% (102/335) of retractions, while 72.2% (243/335) originated from China. Compromised peer review was the most common retraction reason, though 37.9% (127/335) lacked specific justification. Strikingly, 51.1% (172/335) of retracted articles-maintained field citation ratios >1, indicating persistent scholarly influence. Articles in special issues showed significantly faster submission-to-acceptance timelines ( Discussion: This study highlights systemic vulnerabilities in AI-related research publication, particularly concerning peer review integrity and prolonged retraction timelines. The continued citation of retracted articles underscores the need for improved retraction alert systems. These findings call for stronger ethical guidelines and technological safeguards to maintain trust in AI-driven scholarly outputs.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.