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Record W2972582344 · doi:10.1136/bjsports-2019-100957

ICON PART-T 2019–International Scientific Tendinopathy Symposium Consensus: recommended standards for reporting participant characteristics in tendinopathy research (PART-T)

2019· article· en· W2972582344 on OpenAlexaff
Ebonie Rio, Seán Mc Auliffe, Irene M. Kuipers, M. Girdwood, Håkan Alfredson, Roald Bahr, Jill Cook, Brooke K. Coombes, Siu Ngor Fu, Alison Grimaldi, Robert‐Jan de Vos, Jeremy Lewis, Nicola Maffulli, Peter Malliaras, S. Peter Magnusson, Edwin H. G. Oei, Craig Purdam, Jonathan D Rees, Alex Scott, Karin Grävare Silbernagel, Cathy Speed, Inge van den Akker‐Scheek, Bill Vicenzino, Adam Weir, Jennifer Moriatis Wolf, Johannes Zwerver

Bibliographic record

VenueBritish Journal of Sports Medicine · 2019
Typearticle
Languageen
FieldMedicine
TopicTendon Structure and Treatment
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsTendinopathyMedicineMEDLINEPhysical therapyConsensus conferenceAthletesFamily medicineTendonPathologyInternal medicine

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

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)0.525
metaresearch head score (Gemma)0.657
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.475
Threshold uncertainty score0.586

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.5250.657
Meta-epidemiology (narrow)0.0030.006
Meta-epidemiology (broad)0.0080.015
Bibliometrics0.0270.020
Science and technology studies0.0070.010
Scholarly communication0.0200.009
Open science0.0140.021
Research integrity0.0240.015
Insufficient payload (model declined to judge)0.0350.029

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 head0.074
GPT teacher head0.379
Teacher spread0.305 · 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
DomainReporting
GenreMethods

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

Citations95
Published2019
Admission routes1
Has abstractyes

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