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Record W3153605931 · doi:10.1136/bjsports-2020-103512

A novel approach to improve detection of glucocorticoid doping in sport with new guidance for physicians prescribing for athletes

2021· review· en· W3153605931 on OpenAlexaff
Rosa Ventura, Peter T. Daley‐Yates, Irene Mazzoni, Katia Collomp, Martial Saugy, Frank Buttgereit, Olivier Rabin, Mark Stuart

Bibliographic record

VenueBritish Journal of Sports Medicine · 2021
Typereview
Languageen
FieldMedicine
TopicHormonal and reproductive studies
Canadian institutionsWorld Anti-Doping Agency
Fundersnot available
KeywordsAthletesMedicineHarmGlucocorticoidPerformance enhancementAdverse effectAgency (philosophy)Intensive care medicinePhysical therapyPharmacologyPsychologyInternal medicinePhysical medicine and rehabilitation

Abstract

fetched live from OpenAlex

The systemic effect of glucocorticoids (GCs) following injectable routes of administration presents a potential risk to both improving performance and causing harm to health in athletes. This review evaluates the current GC antidoping regulations defined by the World Anti-Doping Agency and presents a novel approach for defining permitted and prohibited use of glucocorticoids in sport based on the pharmacological potential for performance enhancement (PE) and risk of adverse effects on health. Known performance-enhancing doses of glucocorticoids are expressed in terms of cortisol-equivalent doses and thereby the dose associated with a high potential for PE for any GC and route of administration can be derived. Consequently, revised and substance-specific laboratory reporting values are presented to better distinguish between prohibited and permitted use in sport. In addition, washout periods are presented to enable clinicians to prescribe glucocorticoids safely and to avoid the risk of athletes testing positive for a doping test.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.977
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.040
GPT teacher head0.304
Teacher spread0.264 · 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 teacher head, not a consensus.

Study designOther design
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

Citations25
Published2021
Admission routes1
Has abstractyes

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