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Record W2794188900 · doi:10.1017/s0022215117002225

Open access: is there a predator at the door?

2018· editorial· en· W2794188900 on OpenAlexaff
Rakesh K. Chandra, Edward Fisher, Terry M. Jones, Dennis H. Kraus, John H. Krouse, Michael Link, Lawrence R. Lustig, Bert W. O’Malley, Jay F. Piccirillo, Robert J. Ruben, Robert T. Sataloff, Sandra Schwartz, Raj Sindwani, Richard J. Smith, Michael G. Stewart, Peter Weber, D. Bradley Welling, Robin Youngs

Bibliographic record

VenueThe Journal of Laryngology & Otology · 2018
Typeeditorial
Languageen
FieldDecision Sciences
TopicAcademic Publishing and Open Access
Canadian institutionsCanadian Journal of Communication (Canada)
Fundersnot available
KeywordsPredatorContent (measure theory)Computer scienceAction (physics)DatabaseWorld Wide WebMathematicsBiologyPredationEcologyPhysics

Abstract

fetched live from OpenAlex

Open access journals play an increasingly important role in today's world of medical publication, and provide information which would otherwise be difficult or impossible for some to access.Openly sharing peerreviewed information at no cost to the reader can greatly enhance the distribution of legitimate scientific and clinical data.However, there is also an increasing number of journals purporting to serve this mission but acting in a predatory fashion.Here are a few guidelines.

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)0.018
metaresearch head score (Gemma)0.082
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Open science
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.997
Threshold uncertainty score0.150

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.082
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0040.006
Scholarly communication0.0170.008
Open science0.0030.002
Research integrity0.0110.021
Insufficient payload (model declined to judge)0.0450.032

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 head0.088
GPT teacher head0.458
Teacher spread0.370 · 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 designNot applicable
DomainEvaluation
GenreEditorial

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

Citations0
Published2018
Admission routes1
Has abstractyes

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