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Record W2083707261 · doi:10.1089/acm.2009.0176

The Marketing of Dietary Supplements in North America: The Emperor Is (Almost) Naked

2010· article· en· W2083707261 on OpenAlexaff
Norman J. Temple

Bibliographic record

VenueThe Journal of Alternative and Complementary Medicine · 2010
Typearticle
Languageen
FieldMedicine
TopicConsumer Attitudes and Food Labeling
Canadian institutionsAthabasca University
Fundersnot available
KeywordsMedicineHealth benefitsFish <Actinopterygii>Traditional medicineMarketingEnvironmental healthBusinessFishery

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.190
Threshold uncertainty score0.540

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.037
GPT teacher head0.329
Teacher spread0.292 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations16
Published2010
Admission routes1
Has abstractyes

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