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Record W2168387142 · doi:10.1136/bjsm.2010.079822

IOC consensus paper on the use of platelet-rich plasma in sports medicine

2010· article· en· W2168387142 on OpenAlexaff
Lars Engebretsen, Kathrin Steffen, Joseph Alsousou, Eduardo Anitua, Norbert Bachl, R.J.J. Devilee, Peter A. Everts, Bruce Hamilton, Johnny Huard, Peter Jenoure, François Kelbérine, Elizaveta Kon, Nicola Maffulli, Gordon O. Matheson, Omer Mei-Dan, Jacques Ménétrey, Marc J. Philippon, Pietro Randelli, Patrick Schamasch, Martin Schwellnus, Alan Vernec, Geoffrey M. Verrall

Bibliographic record

VenueBritish Journal of Sports Medicine · 2010
Typearticle
Languageen
FieldMedicine
TopicPeriodontal Regeneration and Treatments
Canadian institutionsWorld Anti-Doping Agency
Fundersnot available
KeywordsPlatelet-rich plasmaSports medicineConsensus conferenceMedicinePlateletPathologyInternal medicine

Abstract

fetched live from OpenAlex

Acute and chronic musculoskeletal injuries in sports are common and problematic for both athletes and clinicians. A significant proportion of these injuries remain difficult to treat, and many athletes suffer from decreased performance and longstanding pain and discomfort. In 2008, the International Olympic Committee (IOC) published a consensus document on the importance of molecular mechanisms in connective tissue and skeletal muscle injury and healing. This document predicted an increase in the use of autologous growth factors, as it has indeed happened following that publication.

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)0.037
metaresearch head score (Gemma)0.047
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: Editorial · Consensus signal: none
Teacher disagreement score0.037
Threshold uncertainty score0.198

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0370.047
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0040.004
Science and technology studies0.0020.002
Scholarly communication0.0040.002
Open science0.0060.003
Research integrity0.0160.013
Insufficient payload (model declined to judge)0.0050.005

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 head0.030
GPT teacher head0.267
Teacher spread0.237 · 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
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

Citations278
Published2010
Admission routes1
Has abstractyes

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