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Antioxidants: Regulatory Status

2020· other· en· W4239272476 on OpenAlexaff
Fereidoon Shahidi, HYing Joy Zhong, Priyatharini Ambigaipalan

Bibliographic record

VenueBailey's Industrial Oil and Fat Products · 2020
Typeother
Languageen
FieldChemistry
TopicDye analysis and toxicity
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsChemistryReactive oxygen speciesAntioxidantRadicalQuenching (fluorescence)Reactive nitrogen speciesLipid oxidationFood additiveFood scienceSubstrate (aquarium)BiochemistryChlorineEnvironmental chemistryOrganic chemistryBiology

Abstract

fetched live from OpenAlex

Abstract Oxidation of unsaturated lipids is a major cause of food quality deterioration by giving rise to the development of off‐flavor compounds and loss of nutritional value of food products. Antioxidants are substances that, when present in foods at low concentrations compared with that of an oxidizable substrate, markedly delay or prevent the oxidation of the substrate by quenching free radicals or scavenging oxygen, among others. Antioxidants that fit in this definition include free radical scavengers, inactivators of peroxides, and other reactive oxygen species (ROS), chelators of metal ions, and quenchers of secondary lipid oxidation products that produce rancid odors. Antioxidants have also been used in the health‐related area because of their ability to protect the body against damage caused by ROS, reactive nitrogen species (RNS) and those of reactive chlorine species (RCS). The US Food and Drug Administration (FDA) regulates the claim of antioxidants in nutrient labeling. According to FDA, the antioxidant claim is possible only if there is an established reference daily intake (RDI) and a scientific evidence of antioxidative effect after absorption in the gastrointestinal tract.

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)0.005
metaresearch head score (Gemma)0.007
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.060
Threshold uncertainty score0.199

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0020.001
Scholarly communication0.0050.003
Open science0.0020.002
Research integrity0.0060.003
Insufficient payload (model declined to judge)0.0600.042

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 head0.030
GPT teacher head0.227
Teacher spread0.197 · 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

Citations29
Published2020
Admission routes1
Has abstractyes

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