Bibliographic record
Abstract
Sportsmen have used anabolic steroids since the 1950s and yet it was not until the 1980s that we, as physicians, admitted that they could improve performance. We now find ourselves in the insidious position of being unable to predict convincingly either safety or major health risks with performance-enhancing drug use. The use of performance-enhancing drugs is no longer limited to the elite athlete. In 1993 the Canadian Center for Drug-free Sport estimated that 83 000 children between the ages of 11 and 18 had used anabolic steroids in the previous 12 months. Recent evidence suggests anabolic steroids are now the third most commonly offered drugs to children in the UK, behind cannabis and amphetamines. The role of the physician of today is to regain our position of impartiality and objectivity within both the sporting and general community. Only then will we be able to pursue a harm minimisation strategy designed to convince the public that it is better to be the best you can be naturally. For the majority, the improvement through the use of performance-enhancing drugs can equally be achieved through dietary and training advice. For the elite athlete, what price a gold medal that is tarnished by deceit? Its value then can only lie with the sponsors and politicians, for they can no longer claim to be sportsmen, only entertainers.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".