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Record W2790136216 · doi:10.1016/j.peh.2018.01.001

Doping prevalence among Danish elite athletes

2018· article· en· W2790136216 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenuePerformance Enhancement & Health · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicDoping in Sports
Canadian institutionsnot available
FundersWorld Anti-Doping AgencyAnti Doping Danmark
KeywordsDanishConfidence intervalAthletesElite athletesDemographyMedicineEliteGermanPhysical therapyInternal medicineGeographySociology

Abstract

fetched live from OpenAlex

The objective of this study was to investigate seasonal and all time doping among Danish elite athletes (N = 771, male = 56.5%) and to investigate gender differences. An online survey was conducted (response rate = 57%) which included biographical information as well as randomized response technique questions about seasonal and all-time doping. Concerning last season prevalence, the maximum doping rate was estimated at 30.6% (95% confidence interval 22.6–35.7) and the rate of honest non-dopers was estimated at 69.4%. For the lifetime prevalence of doping, a rate of at least 3.1% dopers (95% confidence interval 0–8.9) and a maximum of 26% (95% confidence interval 13.4–40.8), with a rate of approximately 74% who can reliably be estimated to have never doped throughout their career was identified. No significant gender differences were found. In conclusion, the doping prevalence among Danish elite athletes is similar to that of Dutch and German elite athletes.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.557
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.027
GPT teacher head0.338
Teacher spread0.311 · 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