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Record W2772053435 · doi:10.1002/9781119135388.ch14

Antioxidants in oxidation control

2017· book-chapter· en· W2772053435 on OpenAlexaff
Fereidoon Shahidi, Priyatharini Ambigaipalan

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldMedicine
TopicPhytochemicals and Antioxidant Activities
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsAscorbic acidAntioxidantChemistryPolyphenolLipid oxidationRadicalOrganic chemistryChelationCarotenoidFood scienceBiochemistry

Abstract

fetched live from OpenAlex

Antioxidants are substances present at low concentrations in food or in the body, which markedly delay or inhibit or control the oxidation of oxidizable substrate. Tocopherols/tocotrienols, ascorbic acid, carotenoids, and polyphenols are the traditional natural antioxidants, which are highly concentrated in fruits, vegetables, and grains. Antioxidant mechanisms of action include scavenging of free radicals, chelating of transition metal ion catalysts, reducing hydroperoxides into stable hydroxyl derivatives and interacting synergistically with other reducing compounds. Structural modification of phenolic antioxidants increased their application substantially in more diverse systems, such as fats and oils, lipid-based foods or cosmetic formulas, emulsions, and many biological environments. Ascorbic acid is a water-soluble antioxidant and its mechanism of oxidation inhibition primarily relies on its reducing potential. Ascorbic acid has been known to suppress pigmentation of the skin and decomposition of melanin and improve skin elasticity by promoting the formation of collagen, hence it is used in cosmetic and dermatological products.

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)0.000
metaresearch head score (Gemma)0.000
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: none
Teacher disagreement score0.025
Threshold uncertainty score0.085

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.002
Scholarly communication0.0030.004
Open science0.0010.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0250.017

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 head0.023
GPT teacher head0.273
Teacher spread0.250 · 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

Citations8
Published2017
Admission routes1
Has abstractyes

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