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Record W1596144995 · doi:10.1002/9781118504956.ch12

Role and Importance of Health Claims in the Nutraceutical and Functional Food Markets

2014· other· en· W1596144995 on OpenAlexaff
Alberta N. A. Aryee, Joyce I. Boye

Bibliographic record

Venuenot available
Typeother
Languageen
FieldMedicine
TopicConsumer Attitudes and Food Labeling
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsNutraceuticalHealth claims on food labelsFunctional foodMarketingBusinessHealth benefitsProduct (mathematics)Food productsAdvertisingNovel foodHealth foodScientific evidenceMedicineFood scienceTraditional medicine

Abstract

fetched live from OpenAlex

Several studies have attempted to establish the relationship between nutraceuticals and/or functional foods and a healthier life and/or the prevention of certain diseases. Various countries and jurisdictions have regulatory requirements for the use of health claims on labels and the public advertisement of nutraceuticals and/or functional food products. This is aimed at product safety and to protect consumers from being misled by unsubstantiated claims of the benefits of foods and food products and miraculous cures meticulous scientific evaluation is needed to ensure that health claims made on food labeling and advertising are meaningful and accurate, and will help consumers in making informed choices. The perceived healthiness of functional foods and nutraceutical products is enhanced by the ability to make a health claim, and this is used as a marketing tool worldwide.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.021
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.015
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.021
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.002
Science and technology studies0.0020.008
Scholarly communication0.0090.010
Open science0.0010.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0150.001

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 head0.025
GPT teacher head0.286
Teacher spread0.262 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations5
Published2014
Admission routes1
Has abstractyes

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