Pharmacological and toxicological aspects of performance-enhancing substances
Bibliographic record
Abstract
Organized sport has a history dating back to ancient Greece, but in the early 20th century, pharmaceutical companies expanded the production of remedies offered to treat any health problem. Athletes were free to access whatever substance was available, since there was very little control in sport. During the 50’s, use of anabolic steroids has started. In a paper published in 1973, Silvester proposed a survey of track and field athletes and showed than 68% had utilized anabolic steroids during the 1972 Olympic Games. In the 80’s, Ben Johnson was tested positive for stanozolol during the summer Olympics in Seoul, and this event showed that doping occurred at the highest level in sport. Historians may come to view 1998 as a very special year in the story of drugs in sport. The scandal began in January when a Chinese swimmer was stopped at a routine custom check in Australia with hGH vials in her luggage. During the Tour de France, the Festina affair occurred with a car from the cycling team found full of doping products. In September, the gold champion Florence Griffith Joyner died in her sleep. She was 38…The media reporting of this event asked the question of the responsibility of doping in the death of the athlete. In 1999, the WADA (World antidoping agency) was initiated by the International Olympic Committee based in Canada to promote, coordinate and monitor the fight against drugs in sports. The agency's key activities include scientific research, education, development of anti-doping capacities. Since this period, the WADA has been working closely with international enforcement agencies to uncover doping activities. Among the keys to an effective anti doping program, is the legal definition of doping, but also the publication of the Prohibited List of substances and methods. Of course, the Prohibited List must be an evolving document. According to WADA, the prohibited drugs can be divided into 3 major classes: drugs that are prohibited in and out of competition, drugs prohibited in competition only, and drugs prohibited only in particular sports. These 3 classes are divided into 11 categories, from S0 to S5 for drugs prohibited in and out of competition, S6 to S9 for drugs prohibited in competition and P1 and P2 for drugs prohibited only in particular sports. All performance enhancing drugs are chemicals that promote in any way the athletic performances in humans. Major effects are the following: benefit for muscles, metabolic effects, anabolic effects, bronchodilatation, psychoanaleptic and behavioural effects, hemodilution and increased urinary excretion. But near to these performance enhancing effects, these chemicals also have side effects affecting the brain or the body. Each category of drugs is presented and discussed. Each category is also illustrated by some famous examples.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".