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Record W4214581974 · doi:10.1136/bjsports-2020-102219

Infographic. Consensus recommendations on the classification, definition and diagnostic criteria of hip-related pain in young and middle-aged active adults from the International Hip-related Pain Research Network, Zurich 2018

2020· review· en· W4214581974 on OpenAlexaff
Michael P. Reiman, Rintje Agricola, Joanne L. Kemp, Joshua Heerey, Adam Weir, Pim van Klij, Ara Kassarjian, A. Mosler, Eva Ageberg, Per Hölmich, Kristian Marstrand Warholm, Damian Griffin, Sue Mayes, Karim M. Khan, Kay M. Crossley, Mario Bizzini, Nancy J. Bloom, Nicola C. Casartelli, Laura E. Diamond, Stephanie Di Stasi, Michael K. Drew, Daniel J. Friedman, Matthew Freke, S. Glyn-Jones, Boris Gojanovic, Marcie Harris‐Hayes, Michael A. Hunt, Franco M. Impellizzeri, Lasse Ishøi, Denise Jones, Matthew King, Peter R. Lawrenson, Michael Leunig, Cara L. Lewis, Nicolas Mathieu, Håvard Moksnes, May Arna Risberg, Mark J. Scholes, Adam I. Semciw, Andreas Serner, Kristian Thorborg, Adam Virgile, Tobias Wörner, H Paul Dijkstra

Bibliographic record

VenueBritish Journal of Sports Medicine · 2020
Typereview
Languageen
FieldMedicine
TopicHip disorders and treatments
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsHip painMedicineInfographicPhysical therapyPhysical medicine and rehabilitationComputer scienceData mining

Abstract

fetched live from OpenAlex

**Please note that there are multiple authors for this article therefore only the name of the first 30 including Federation University Australia affiliate “Michael Drew" is provided in this record**

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)0.021
metaresearch head score (Gemma)0.039
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.033
Threshold uncertainty score0.113

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.039
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0060.011
Bibliometrics0.0200.010
Science and technology studies0.0010.001
Scholarly communication0.0040.004
Open science0.0080.005
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0330.018

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 head0.094
GPT teacher head0.342
Teacher spread0.249 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations4
Published2020
Admission routes1
Has abstractyes

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