The role of banned substance residue analysis in the control of dietary supplement contamination
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.
Bibliographic record
Abstract
The potential for contaminated dietary supplements to result in a failed doping test remains a concern for athletes, trainers, and sporting authorities despite improvements to regulatory guidelines. Previous surveys of readily available supplements confirm that many are contaminated with steroids and stimulants prohibited for use in elite sport. Suggested responses to this issue include the complete avoidance of all supplements. Many athletes, however, use nutritional supplements to achieve effective training and also to ensure that daily nutritional requirements are met (e.g. recommended levels of vitamins and minerals). This ensures that the use of supplements is and will remain the norm for a range of sports. As a result, an alternative approach of rigorous testing of materials destined for use by elite athletes has been introduced in several countries. While the testing of final product for banned substances may help mitigate the problem, it will not help to remove the underlying issue of contamination. In this article we describe an alternative approach that uses appropriate quality assurance procedures backed up by testing to remove sources of contamination. The decrease in the incidence of contamination amongst supplement companies adopting such a system is explained, and contrasted with the relatively high incidences of contamination found in products that are not part of a quality system. These findings are of key importance to both supplement manufacturers and those involved in advising athletes about supplement use.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it