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Record W2900654612 · doi:10.2106/jbjs.17.01569

Predatory Publishing in Orthopaedic Research

2018· article· en· W2900654612 on OpenAlexaff
James Yan, Hassan Baldawi, Johnathan R. Lex, Gabriel Simchovich, Louis-Philippe Baisi, Anthony Bozzo, Michelle Ghert

Bibliographic record

VenueJournal of Bone and Joint Surgery · 2018
Typearticle
Languageen
FieldDecision Sciences
Topicscientometrics and bibliometrics research
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPublishingDirectoryCitationLibrary sciencePublicationWeb of scienceComputer scienceWorld Wide WebMEDLINEPolitical scienceAdvertisingBusinessLaw

Abstract

fetched live from OpenAlex

BACKGROUND: The open-access model has changed the landscape of academic publishing over the last 20 years. An unfortunate consequence has been the advent of predatory publishing, which exploits the open-access model for monetary gain by collecting publishing fees from authors under the pretense of being a legitimate publication while providing little-to-no peer review. This study aims to investigate the predatory publishing phenomenon in orthopaedic literature. METHODS: We searched Beall's List of Predatory Journals and Publishers and another list of predatory journals for journal titles that are possibly related to orthopaedics. We then searched their web sites for the following information: total number of articles published, journal country of origin, author country of origin, article processing charge (APC), quoted review time, and location of the listed headquarters. We also reported the article quality of a random sample of these journals. We consulted InCites Journal Citation Reports to determine the number of nonpredatory orthopaedic publications that are indexed, and we manually searched a random sample of these legitimate journals for Beall's criteria. Additionally, we searched the Directory of Open Access Journals (DOAJ) and PubMed databases for any possible predatory journal titles. RESULTS: We found 104 suspected predatory publishers, representing 225 possible predatory journals. One journal was indexed in the DOAJ, and 20 were indexed in PubMed. Review time was not identified for 56.2% of the journals, and 36.5% quoted a review time of <1 month. Nearly half of the listed addresses of the publishers were either unsearchable or led to residential or empty lots. Eighty-two legitimate journals were identified. The median APC was $420 for predatory journals and $2,900 for legitimate journals. We found that a random sample of the legitimate journals published studies with higher reporting standards, but a few also contained 1 criterion that is found on Beall's list. CONCLUSIONS: This study highlights the scope of orthopaedic predatory publishing. Possibly predatory journals outnumber legitimate orthopaedic journals. Orthopaedic surgeons should be aware of the suspected predatory journals and consult available online tools to identify them because distinguishing them from legitimate journals can be a challenge.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.046
metaresearch head score (Gemma)0.243
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.996
Threshold uncertainty score0.246

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0460.243
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0210.032
Science and technology studies0.0050.013
Scholarly communication0.0150.011
Open science0.0030.009
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0120.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.791
GPT teacher head0.583
Teacher spread0.209 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designObservational
DomainEvaluation
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations56
Published2018
Admission routes1
Has abstractyes

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