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Record W2140164253 · doi:10.1093/anatox/35.9.613

Investigating the Use of Stimulants in Out-of-Competition Sport Samples

2011· article· en· W2140164253 on OpenAlexaff
Thierry Boghosian, Irene Mazzoni, Osquel Barroso, Olivier Rabin

Bibliographic record

VenueJournal of Analytical Toxicology · 2011
Typearticle
Languageen
FieldMedicine
TopicHormonal and reproductive studies
Canadian institutionsWorld Anti-Doping Agency
Fundersnot available
KeywordsAthletesCompetition (biology)AlertnessAgency (philosophy)PsychologyMedicineApplied psychologyPharmacologyPhysical therapy

Abstract

fetched live from OpenAlex

The List of Prohibited Substances and Methods (the List), an International Standard published yearly by the World Anti-Doping Agency (WADA), determines which substances and methods are prohibited in sport in- and out-of-competition. Stimulants are included within drug class S.6 under the in-competition testing section of the List. Athletes may be tempted to use stimulants as ergogenic aids in-competition in order to temporarily improve their mental and/or physical functions by increasing alertness, aggressiveness, motivation, locomotion, heart rate, and reducing fatigue. The Prohibited List Expert Group, responsible for the maintenance of the List, approved WADA funding for a two-year study to determine whether athletes were also using stimulants to benefit from their performance-enhancing effects during the training phase between competitions (i.e., out-of-competition). This study, involving 11 WADA-accredited laboratories, found that the use of stimulants by athletes during training was not significantly prevalent (0.36% of positive findings), suggesting that this issue does not, at the moment, pose a further challenge to the fight against doping in sport. In addition, the study supports the current structure in the Prohibited List that differentiates banned substances into the in- and out-of-competition classifications.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.164

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.242
GPT teacher head0.350
Teacher spread0.109 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations12
Published2011
Admission routes1
Has abstractyes

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