The Problematic Paper Screener automatically selects suspect publications for post-publication reassessment

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WCRI 2022: 7th World Conference on Research Integrity, Cape Town, South Africa. 29 May – 1 June 2022

The ‘Problematic Paper Screener’ automatically selects suspect publications

for post-publication (re)assessment

Guillaume Cabanac · Cyril Labbé · Alexander Magazinov

Objective:

Post publication assessment remains necessary to check erroneous or fraudulent scientific publications.

We present an online platform, the ‘Problematic Paper Screener’ (PPS) that leverages both automatic

machine detection and human assessment to identify and flag already published problematic articles. We

provide a new effective tool to curate the scientific literature.

Method:

PPS combs the scientific literature for a variety of research integrity issues. Malpractices are automatically

identified thanks to specific ‘fingerprint-queries’ submitted to the academic search engine Dimensions.ai.

Peer judgement can then confirm (or refute) the status of suspect papers. The public online interface

allows public users to propose new ‘fingerprints’.

Results:

As of today (Oct. 2021) the PPS (https://www.irit.fr/~Guillaume.Cabanac/problematic-paper-screener)

lists papers containing meaningless computer-generated texts (N=264 SCIgen, 11 Mathgen, 4 SBIR). For

this kind of malpractice, ‘fingerprint-queries’ are specific sequences of words extracted from the

probabilistic context free grammars like ‘though many skeptics said it couldn't be done’. The PPS also lists

papers containing suspected plagiarized passages by automated synonymizing and automated

paraphrasing. These papers feature ‘tortured phrases’ like ‘fake neural organization’ instead of ‘artificial

neural network’. The PPS uses a set of 276 tortured phrases as fingerprint-queries to identify (N=1694)

problematic papers. The PPS queries Dimensions.ai regularly to identify new suspects among recently

published/indexed papers. The PPS public online interface provides public users with the necessary

information to assess suspected papers: access links (Dimension.ai record, DOI…), set of fingerprints found

in the full text, link to existing PubPeer posts... User feedback is a means to both assess papers and identify

new fingerprints/tortured phrases. Among the public list of suspected problematic papers (N=2088), 744

have been classified as problematic by various users and 1344 are still waiting for human assessments.

Conclusion:

The ‘Problematic Paper Screener’ automatically retrieves suspected published papers for scientists to

reassess. The fingerprint-query approach is effective to identify computer-generated papers and

synonymized plagiarism. In the future the approach will be tested for other problematic practices, such

as the reporting of misidentified biological materials.

___________________

Guillaume Cabanac

University of Toulouse, Computer Science Department, IRIT UMR 5505 CNRS, 31062 Toulouse, France

E-mail: guillaume.cabanac@univ-tlse3.fr

ORCID: 0000-0003-3060-6241

Cyril Labbé

Univ. Grenoble Alpes, CNRS, Grenoble INP, LIG, 38000 Grenoble, France

E-mail: cyril.labbe@univ-grenoble-alpes.fr

ORCID: 0000-0003-4855-7038

Alexander Magazinov

Yandex, 82 Sadovnicheskaya str., Moscow 115035, Russia

E-mail: magazinov-al@yandex.ru

ORCID: 0000-0002-9406-013X

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WCRI2022:7thWorldConferenceonResearchIntegrity,CapeTown,SouthAfrica.29May–1June2022The‘ProblematicPaperScreener’automaticallyselectssuspectpublicationsforpost-publication(re)assessmentGuillaumeCabanac·CyrilLabbé·AlexanderMagazinovObjective:Postpublicationassessmentremainsnecessarytocheckerroneousorf...

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The Problematic Paper Screener automatically selects suspect publications for post-publication reassessment

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