The Marketing of Dietary Supplements in North America: The Emperor Is (Almost) Naked
Bibliographic record
Abstract
BACKGROUND: Many different dietary supplements are being sold in North America. The quality of the evidence supporting their efficacy covers a wide spectrum: Some are based on solid science (such as vitamin D and fish oil), whereas with most supplements there is little or no supporting evidence. Types of supplements commonly sold include exotic fruit juices (such as goji juice) and single herbs or mixture of herbs. Common claims made in support of particular supplements are that they are rich in antioxidants, induce detoxification, stimulate the immune system, and cause weight loss. Supplements are commonly sold through health food stores and by multilevel marketing. Sales may be promoted using bulk mail ("junk mail"), spam e-mails, and Web sites. A large part of marketing is based on claims that are blatantly dishonest. CONCLUSIONS: Whereas supplements for which good supporting evidence exists generally cost around $3-$4 per month, those that are heavily promoted for which there is little supporting evidence cost about $20-$60 per month. The major cause of this problem in the United States is weakness of the law. There is an urgent need for stricter regulation and for giving better advice to the general public.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.017 | 0.003 |
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".