A recent study published in The BMJ has revealed a significant issue in cancer research, where nearly ten percent of the papers screened could potentially originate from paper mills. This alarming statistic indicates that cancer research is a major target for fraudulent companies that produce low-quality or fabricated studies. The study highlights the importance of using advanced tools to identify and flag such papers, ensuring the integrity of scientific literature(1).
Over the last two decades, the scientific literature has been flooded by low-quality research papers produced by for-profit organizations, known as “paper mills”. It is estimated that suspected paper mill products account for 2 to 46 percent of manuscripts submitted to scientific journals, with the estimated rate of problematic articles in biomedical research reaching nearly six percent in 2023(2,3).
Open-access journals can make science available to anyone with an internet connection, and many researchers embrace this idea. But without the academic librarians who typically manage journal subscriptions and, in the process, perform additional steps to verify journals’ credibility, the system can be vulnerable to exploitation. For instance, some journals charge authors a large fee in exchange for near-instant publication with an expedited – or sometimes absence of – peer review, which can severely compromise the quality of published scientific works(4).
Published in the medical journal The BMJ, the study titled “Machine learning-based screening of potential paper mill publications in cancer research: methodological and cross-sectional study” analyzed 2.6 million cancer research papers published between 1999 and 2024. Using a machine learning tool, researchers found that nearly 10% of these papers show strong textual similarities to studies known to be produced by so-called “paper mills”, which are the organizations that sell fabricated or low-quality research for profit. The findings suggest that the problem is not marginal, and may be affecting the evidence base of cancer science(5).
What are paper mills in scientific research?
Paper mills are commercial operations that manufacture scientific papers on demand. For a price, they can offer researchers anything from authorship slots to fully written manuscripts, often complete with fabricated data, images and references.
To operate at scale, these organizations rely on templates, recycling sentence structures, phrases and study designs while swapping in different genes, proteins or cancer types. The result can appear legitimate at first glance, but may be fundamentally unreliable(6).
In conclusion, this problem has also been reported in Romania, especially since promotion in the scientific hierarchy often depends on such publications. That is why I believe that any journal – even though it does not charge money for publications – is credible if it has an AI verification system and a team of reviewers known in the scientific world. Rather than resorting to all kinds of pseudoscientific subterfuges or paid studies carried out by nonprofit companies, it would be better to seek sponsorship for such “free” journals, but with AI verification and a team of internationally recognized reviewers.
Bibliografie
1. Careaga DMBL. Nearly Ten Percent of Cancer Papers Flagged as Potentially Fake. The Scientist. https://www.the-scientist.com/nearly-ten-percent-of-cancer-papers-flagged-aspotentially-fake-74185
2. COPE & STM. Papers Mills – Research report from COPE & STM. 2022. https://members.publicationethics.org/sites/default/files/paper-mills-cope-stm-research-report.pdf
3. Sabel BA, Knaack E, Gigerenzer G, Bilc MI. Fake publications in biomedical science: red-flagging method indicates mass production. Naunyn Schmiedebergs Arch Pharmacol. 2026;399(2):2943-2955.
4. AI analysis shows fake studies may be flooding cancer research worldwide. Health News – Business Standard. https://www.business-standard.com/health/ai-analysis-fake-studiesflooding-cancer-research-worldwide-126020900323_1.html
5. Scancar B, Byrne JA, Causeur D, Barnett AG. Machine learning based screening of potential paper mill publications in cancer research: methodological and cross sectional study. BMJ. 2026;392:e087581.
6. Lius A. AI Helps Flag Potentially Problematic Journals for the First Time. The Scientist. https://www.the-scientist.com/ai-helps-flag-potentially-problematic-journals-for-the-firsttime-73494