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Record W4389568575 · doi:10.31579/2642-9756/204

Obesity Policy: Opportunities for Functional Food Market Growth

2023· article· en· W4389568575 on OpenAlexfundno aff
Rehan Haider, Asghar Mehdi

Bibliographic record

VenueWomen Health Care and Issues · 2023
Typearticle
Languageen
FieldMedicine
TopicConsumer Attitudes and Food Labeling
Canadian institutionsnot available
FundersUniversity of KarachiUniversity of Calgary
KeywordsProduct (mathematics)BusinessPublic healthMarketingMedicineNursing

Abstract

fetched live from OpenAlex

The comprehensive rise in obesity rates has incited a reevaluation of society's well-being strategies and has opened new freedom in meat manufacturing. This study investigates the vitally related middle from two points: existing corpulence processes and the development of the occupied feed. By resolving existent research, residency rules, and production styles, we aim to resolve these two rules and understand the potential for collaboration. Key Findings: Public Health Crisis: Obesity has improved an imperative worldwide change in happiness, followed by main socioeconomic and well-being-following results. Governments have mainly approved the need for active processes to address this issue. Functional Foods: The billing of occupied food, including foodstuffs protecting the following energy-boosting components, has made the main progress. Consumers chase production that offers strength benefits to further their fundamental fare. Regulatory Environment: Governments are developing and invigorating strategies to combat obesity. These include designating necessities, oxygen taxes, limits on propaganda morbid meals, counterfeiting two challenges, and providing room for active food production. Market Expansion: The demand for occupied lunches is increasing in reaction to raised information. As a result, there is prime independence for actively begun manufacturers to touch their fruit offerings that follow the obesity tactics aims. Innovation and Product Development: The display of occupied foods is developing swiftly, followed by changes in crop incidents, containing the addition of bioactive compounds and digestive augmentations to support burden reduction and overall well-being. Public-Private Collaboration: Collaboration comes from two points: community health specialists and active food production, which commit to advancing the result of improved health harvests and more active process exercises.

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)0.000
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.399
Threshold uncertainty score0.349

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
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 head0.079
GPT teacher head0.342
Teacher spread0.263 · 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
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

Citations0
Published2023
Admission routes1
Has abstractyes

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