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Record W3157747276 · doi:10.24926/iip.v12i2.3694

A Comparison of Current Regulatory Frameworks for Nutraceuticals in Australia, Canada, Japan, and the United States.

2021· review· en· W3157747276 on OpenAlexaboutno aff
Jessica Blaze

Bibliographic record

VenueINNOVATIONS in pharmacy · 2021
Typereview
Languageen
FieldMedicine
TopicConsumer Attitudes and Food Labeling
Canadian institutionsnot available
Fundersnot available
KeywordsNutraceuticalHarmonizationContext (archaeology)BusinessGovernment (linguistics)Product (mathematics)Medical prescriptionMarketingBiotechnologyMedicinePharmacologyBiology

Abstract

fetched live from OpenAlex

The nutraceutical market is growing and the demand for products is increasing. Consumers are looking for cheaper alternatives to prescription medications as well as health products to supplement their dietary intake on a regular basis. Many countries classify these products into different categories based on their health claims. The purpose of this review is to compare and contrast the differences of regulatory frameworks in countries of similar status in regard to nutraceutical products: vitamins, minerals, herbal supplements, and probiotics. This review also takes into consideration the aspects of nutraceutical safety in relation to government regulations. It is evident that further discussion is indicated with regard to the harmonization of nutraceutical product regulation in a global context in order to promote and protect public health. This literature review selected 27 documents for a review using a systematic search of internet databases and search engines including PUBMED and Google Scholar. These documents were reviewed and synthesized for data relating to nutraceutical regulation within the four different countries of focus. Outcomes included information on safety and toxicity, drug interactions, classification of products, and regulatory processes for nutraceutical product approval in each country.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.979
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
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 head0.228
GPT teacher head0.515
Teacher spread0.287 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations45
Published2021
Admission routes1
Has abstractyes

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