Tribulus terrestris and Sport Performance: A Quantitative and Qualitative Evaluation of Its Advertisement and Availability via Online Shopping in Six Different Countries
Bibliographic record
Abstract
Dietary supplements are commonly used among athletes, and the Internet may be an easy source of these products. Tribulus terrestris is an herbal supplement with multiple properties. Of interest to athletes are reports that its consumption can lead to muscle mass gain and a faster recovery process. The objective of this cross-sectional study was to determine the availability of Tribulus terrestris via the Internet in six countries (Canada, Puerto Rico, Russia, Spain, Ukraine, and the United States of America) via a specifically designed computer program. The characteristics of the websites selling this substance, the country from which it can be purchased, the route of administration, and recommendations for its use were analyzed. The results of the study show that this supplement is marketed mainly in Russia, Ukraine, and Spain on many websites that are mostly dedicated to sports products. Just over half of the webpages (59.14%) identified only distribute this supplement within the same country. The main claims for its consumption refer to sports performance benefits, but there are also claims that it may improve male hormone levels and sexual function. Athletes should be encouraged to seek professional advice prior to ingesting this supplement to ensure that it is suitable for their specific training and sports objectives.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".