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Record W4416113614 · doi:10.1136/bjsports-2025-111063

Advancing global equity, diversity and inclusion in sport and exercise medicine consensus and research: deliberate, thoughtful steps from the FAIR consensus

2025· article· en· W4416113614 on OpenAlexaff
Brooke Patterson, Nana Akua Achiaa Adom-Aboagye, Naama Constantini, Carole Akinyi Okoth, Yuka Tsukahara, Dina C. Janse van Rensburg, Oluwatoyosi B. A. Owoeye, L. Gracias, M. Haberfield, Jackie L. Whittaker, H Paul Dijkstra, Tara-Leigh McHugh, Carolyn A. Emery, Kay M. Crossley

Bibliographic record

VenueBritish Journal of Sports Medicine · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics and Physical Performance
Canadian institutionsUniversity of CalgaryResearch CanadaUniversity of British Columbia
Fundersnot available
KeywordsInclusion (mineral)Diversity (politics)Sports medicineAlternative medicineMEDLINEPhysical activityIntegrative medicine

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.455
metaresearch head score (Gemma)0.458
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Open science
Consensus categoriesMetaresearch
DomainCandidate signal: Incentives · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.991
Threshold uncertainty score0.672

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.4550.458
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0060.003
Bibliometrics0.0040.002
Science and technology studies0.0170.061
Scholarly communication0.0330.032
Open science0.0090.046
Research integrity0.0490.071
Insufficient payload (model declined to judge)0.0070.001

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 head0.019
GPT teacher head0.312
Teacher spread0.293 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
DomainIncentives
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

Citations1
Published2025
Admission routes1
Has abstractno

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