MétaCan
Menu
Back to cohort
Record W4412818921 · doi:10.56028/aetr.14.1.1374.2025

The Impact and Regulation of Performance-Enhancing Drugs in Sports

2025· article· en· W4412818921 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAdvances in Engineering Technology Research · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicDoping in Sports
Canadian institutionsCanadian Rheumatology Association
Fundersnot available
KeywordsBusiness

Abstract

fetched live from OpenAlex

Performance-enhancing drugs (PEDs) have been repeatedly banned in sport for a variety of reasons. The use of PEDs not only violates sports ethics but also creates serious health risks for athletes, such as cardiovascular injuries and mental disorders. In particular, the systematic use of PEDs in some countries or regions with the support of coaches and the state undermines the integrity and fairness of sports, and at the same time, can be detrimental to the sports economy. Although education on the prohibition of PED use is currently very widespread and has raised awareness of the dangers of PED use, the current education system fails to address psychological stressors such as failure anxiety. To further increase awareness of the prohibition of PED use, this review calls for multifaceted reforms, including evidence-based education for youth, advanced detection technologies (e.g., blockchain), and institutional accountability for federations and sponsors. These measures aim to shift the culture of sport towards integrity and athlete well-being rather than performance shortcuts.

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.

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)0.003
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 score0.134
Threshold uncertainty score0.195

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
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 head0.009
GPT teacher head0.368
Teacher spread0.359 · 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