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Record W4200464617 · doi:10.1080/10408398.2021.2019672

Schemes for enhanced antioxidant stability in frying meat: a review of frying process using single oil and blended oils

2021· review· en· W4200464617 on OpenAlexaff
Ju Shen, Min Zhang, Linlin Zhao, Arun S. Mujumdar, Haixiang Wang

Bibliographic record

VenueCritical Reviews in Food Science and Nutrition · 2021
Typereview
Languageen
FieldChemistry
TopicEdible Oils Quality and Analysis
Canadian institutionsMcGill University
FundersKey Lab of Advanced Optical Manufacturing Technologies of Jiangsu ProvinceYangzhou City Agricultural Key R and D ProgramGovernment of Jiangsu Province
KeywordsFood scienceDeep fryingEdible oilChemistry

Abstract

fetched live from OpenAlex

Deep-fried meat products are widely popular. However, harmful compounds produced by various chemical reactions during frying have been shown to be detrimental to human health. It is of great necessity to raise practical suggestions for improving the oxidation problem of frying oils and frying conditions in some aspects. Vegetable oils are not as thermally stable as saturated fats, and blended oils have higher thermal stability than single oil. In this review, we discussed the oxidation problems frying oils and meats are subject to during frying, starting from the oil oxidation mechanism, the effects of different oils and fats on the quality of different fried meats under different conditions were concluded to alleviate the oxidation problem, to highlight the necessity of applying blended oils for frying, and effective antioxidants added to frying oils are also introduced, that would provide more convenient and practical options for obtaining higher quality of fried meat products and offer better understanding of the potential of blended frying oils for frying meat 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 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)0.004
metaresearch head score (Gemma)0.014
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.385
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
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 head0.195
GPT teacher head0.440
Teacher spread0.244 · 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.

Study designSystematic review
Domainnot available
GenreReview

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

Citations14
Published2021
Admission routes1
Has abstractyes

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