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The article offers information on the intersection of AI, research, and its impact on scientific literature. Topics include concerns about the ethical implications of AI-generated content, fraudulent research papers created by paper mills, and the increasing retractions of scientific literature. The author reflects on the potential consequences of the rise in spurious publications on research impact metrics and raises concerns about research integrity.

The article explores Clarivate's Institute for Scientific Information (ISI) proposed a new Collaborative CNCI (Collab-CNCI) indicator to analyze the credit authors of academic papers receive via citations. In its report, "Making It Count: Research Credit Management in a Collaborative World," ISI confirms that highly collaborative papers can distort summary results at a national and institutional level.

The article reports that research reproducibility, getting consistent results with the same set of data, code, and method described in the original research paper, is central to trustworthy scientific research. It reports that to address the growing need of research reproducibility, scholarly publishers have implemented features to access data, code, and experiments in their scholarly publication platforms.