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Record W4303645047 · doi:10.3390/foods11193043

Role and Importance of Functional Food Packaging in Specialized Products for Vulnerable Populations: Implications for Innovation and Policy Development for Sustainability

2022· article· en· W4303645047 on OpenAlexaboutno aff
Melvin A. Pascall, Kris DeAngelo, Julie Richards, Mary Beth Arensberg

Bibliographic record

VenueFoods · 2022
Typearticle
Languageen
FieldMedicine
TopicConsumer Attitudes and Food Labeling
Canadian institutionsnot available
Fundersnot available
KeywordsSustainabilityLegislatureBusinessProduct (mathematics)Sustainable developmentNew product developmentRisk analysis (engineering)MarketingPolitical scienceBiologyEcology

Abstract

fetched live from OpenAlex

Specialized products can be needed to help meet the nutrition requirements of vulnerable populations, including infants and young children, those who are ill, and older adults. Laws and regulations delineate distinct categories for such products including medical foods or formulated liquid diets, foods for special dietary use (FSDUs), infant formulas, and natural health products (NHPs). Yet, the literature is limited regarding the role and importance of functional and sustainable packaging for specialized products. This perspective review describes these unique product categories and the role of packaging as well as regulatory considerations. Furthermore, reviewed are how waste reduction strategies and emerging legislative/regulatory policies in the United States and Canada may not adequately address the functional packaging requirements for specialized products. The paper concludes by offering perspectives for emerging innovations and policy development for sustainability.

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)0.012
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.010
Scholarly communication0.0090.009
Open science0.0010.004
Research integrity0.0070.004
Insufficient payload (model declined to judge)0.0060.000

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 head0.064
GPT teacher head0.347
Teacher spread0.283 · 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 designQualitative
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

Citations62
Published2022
Admission routes1
Has abstractyes

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