Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".