baptscc.bsky.social
@baptscc.bsky.social
📤 11
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Data scientist | Engineer Aspiring metascience researcher
pinned post!
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.
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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...
https://www.bmj.com/content/392/bmj-2025-087581
about 1 month ago
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baptscc.bsky.social
The Conversation France
6 days ago
Les fausses publications scientifiques menacent de submerger la recherche contre le cancer
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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.
http://dlvr.it/TR9qrc
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reposted by
baptscc.bsky.social
Rhea Liang
16 days ago
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/...
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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...
https://www.bmj.com/content/392/bmj-2025-087581?nbd_source=adestra&nbd=34f9ed430af73135d067b269a6b46ca61cd8ca53e29f94ee7fe37f095c4629ce&uaa_id=34f9ed430af73135d067b269a6b46ca61cd8ca53e29f94ee7fe37f095c4629ce&utm_campaign=This%20week%20in%20The%20BMJ%20-%20Fortnightly%20manual%20alert&utm_medium=email&utm_source=adestra
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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.
loading . . .
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...
https://www.bmj.com/content/392/bmj-2025-087581
about 1 month ago
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10
2
reposted by
baptscc.bsky.social
Jennifer Byrne
about 1 month ago
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!
add a skeleton here at some point
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reposted by
baptscc.bsky.social
AusHSI
about 1 month ago
“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.
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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”.
https://www.qut.edu.au/news?id=203173
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reposted by
baptscc.bsky.social
Robin Blythe
about 1 month ago
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/...
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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...
https://www.bmj.com/content/392/bmj-2025-087581
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