FR: Avec David Causeur, nous avons publié un court commentaire dans médecine/sciences à propos de notre article du BMJ sur les fabriques à articles scientifiques. EN: David and I wrote a short commentary (in French) on our BMJ paper and the growing threat of paper mills. 📄 doi.org/10.1051/meds...

New study: Articles from #PaperMills can get "50 to 100% more #citations than other papers" even with fewer downloads. One cause for the extra citations is mutual citation by the same papers. Primary source (preprint) www.biorxiv.org/content/10.6... Summary in Nature www.nature.com/articles/d41...

Suspected distortion of citations in high-impact cancer journals

Research and scholarship are shaped by article citations, which underpin the communication of ideas, assignment of credit, journal impact factors, and author career progression. Given their key influe...

biorxiv.org

Cancer research articles with telltale signs of being produced by paper mills garner double the number of citations than do genuine papers in the field go.nature.com/4axPpGN

Paper mill cancer studies get double the number of citations as genuine papers

Potentially fraudulent papers often cite each other and could be inflating the impact factor of journals in which they are published.

go.nature.com

Another reason to distrust journal-based citation metrics: "Suspected #papermill articles…cited – and were cited by – other suspected paper mill articles…The resulting citations…measurably inflated journal citation metrics." www.biorxiv.org/content/10.6... #Citations #JIF #ScholComm

New @biorxivpreprint.bsky.social preprint led by @pranujanp.bsky.social, studying errors such as incorrect primer sequences and contaminated #CellLines in #circRNA papers in high impact factor journals. We found reagent errors in 51% of n=118 circRNA papers in high IF journals in 2022 (1/4)🧪

New preprint showing that suspected paper mill papers get more citations (50 to 100% more) than non-suspect papers, but have fewer readers. This odd pattern is explainable by the mills citing their past papers in their new papers. www.biorxiv.org/content/10.6...

Suspected distortion of citations in high-impact cancer journals https://www.biorxiv.org/content/10.64898/2026.05.25.727627v1

New @biorxivpreprint.bsky.social preprint on suspected citation manipulation by #PaperMills in molecular oncology, with Baptiste Scancar, David Causer @institutagro.bsky.social & @aidybarnett.bsky.social @aushsi.bsky.social @sydney.edu.au 🙏 @nhmrc.bsky.social for💰 🧪 www.biorxiv.org/content/10.6...

2,6 millions d'articles de cancérologie screenés... 260 000 frauduleux... 10% des papiers de recherche en cancérologie de ces dernières années sont frauduleux... Petite pensée à notre PhD grocervo qui l'avait pondu un thread pour dire que tout cela était marginal... www.bmj.com/content/392/...

Machine learning based screening of potential paper mill publications in cancer research: methodological and cross sectional study

Objectives To train and validate a machine learning model to distinguish paper mill publications from genuine cancer research articles, and to screen the cancer research literature to assess the preva...

bmj.com

Les fausses publications scientifiques menacent de submerger la recherche contre le cancer

Les fausses publications scientifiques menacent de submerger la recherche contre le cancer

Une étude récente pointe un chiffre alarmant : plus de 250 000 articles scientifiques liés au cancer pourraient avoir été fabriqués de toutes pièces entre 1999 et 2024.

dlvr.it

Machine learning-based screening for publications from (often AI-boosted) paper mills feels dystopian already. But even more dystopian is the pick-up rate in cancer literature- nearly 1 in 10 papers (9.87%). Over 260,000 individual papers in all. 😱 #MedSky www.bmj.com/content/392/...

Machine learning based screening of potential paper mill publications in cancer research: methodological and cross sectional study

Objectives To train and validate a machine learning model to distinguish paper mill publications from genuine cancer research articles, and to screen the cancer research literature to assess the preva...

bmj.com

I am thrilled to announce that my first-ever paper has been published in @bmj.com. It is available here: www.bmj.com/content/392/... I thank my colleagues @aidybarnett.bsky.social, @jabyrnesci.bsky.social and David Causeur for this opportunity and their support.

Machine learning based screening of potential paper mill publications in cancer research: methodological and cross sectional study

Objectives To train and validate a machine learning model to distinguish paper mill publications from genuine cancer research articles, and to screen the cancer research literature to assess the preva...

bmj.com

Thanks so much to @baptscc.bsky.social, recently arrived here, for his brilliant work as first author on this paper (also his first publication). Follow him, he's going places!

Jennifer Byrne@jabyrnesci.bsky.social · 8mo ago

How many #CancerResearch papers may have been contributed to the literature by #PaperMills? We try to put numbers to this problem in our @bmj.com paper by @aidybarnett.bsky.social @aushsi.bsky.social & colleagues. Thank-you @nhmrc.bsky.social for funding @sydney.edu.au www.bmj.com/content/392/...

“If fabricated studies make their way into the evidence base, they can mislead real scientists and ultimately slow progress for patients." Published in The BMJ, a new AI tool developed by @aidybarnett.bsky.social and colleagues has exposed the scale of fake studies flooding cancer research.

New tool exposes scale of fake research flooding cancer science

A new machine learning tool has identified more than 250,000 cancer research papers that may have been produced by so-called “paper mills”.

qut.edu.au

Congrats to @aidybarnett.bsky.social, Baptiste and team on this important #metaresearch paper. I got to see the early analysis stages of this work and have been waiting with baited breath for it to be published: www.bmj.com/content/392/...

Machine learning based screening of potential paper mill publications in cancer research: methodological and cross sectional study

Objectives To train and validate a machine learning model to distinguish paper mill publications from genuine cancer research articles, and to screen the cancer research literature to assess the preva...

bmj.com