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Record W2899296203 · doi:10.1111/1750-3841.14375

Effect of Various Hot‐Air Drying Processes on Clam <i>Ruditapes philippinarum</i> Lipids: Composition Changes and Oxidation Development

2018· article· en· W2899296203 on OpenAlexaff
Zhong‐Yuan Liu, Dayong Zhou, Xin Zhou, Fawen Yin, Qi Zhao, Hongkai Xie, Deyang Li, Beiwei Zhu, Tong Wang, Fereidoon Shahidi

Bibliographic record

VenueJournal of Food Science · 2018
Typearticle
Languageen
FieldNursing
TopicFatty Acid Research and Health
Canadian institutionsMemorial University of Newfoundland
FundersOcean Public Welfare Scientific Research Project
KeywordsRuditapesTBARSLipid oxidationChemistryPolyunsaturated fatty acidFood sciencePeroxide valuePhospholipidThiobarbituric acidPhosphatidylcholinePeroxideFatty acidBiochemistryLipid peroxidationAntioxidantOrganic chemistryBiologyFishery

Abstract

fetched live from OpenAlex

Clam Ruditapes philippinarum was processed by hot-air drying and the changes of its lipids were evaluated by analyzing lipid classes, phospholipid classes, fatty acids, as well as oxidation parameters including peroxide value (POV), thiobarbituric acid-reactive substances (TBARS) value, total oxidation value (TOTOX), and oxidation test (OXITEST). The hot-air drying process reduced the contents of triacylglycerol, phosphatidylcholine, and phosphatidylethanolamine, indicating the hydrolysis of lipids. Meanwhile, the hot-air drying process significantly decreased the proportion of n-6 polyunsaturated fatty acid (PUFA), and consequently increased the PUFA ratio of n-3/n-6. Interestingly, the POV, TBARS and TOTOX decreased after the hot-air drying process. However, significant decline of the induction period for the dried clam tissue at elevated temperatures indicated their higher oxidation level, poor oxidative stability and reduction of shelf-life. Therefore, OXITEST method turned out to be an effective tool for estimating the level of lipid oxidation for hot-air dried clam.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.318
Teacher spread0.296 · 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 designBench or experimental
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

Citations21
Published2018
Admission routes1
Has abstractyes

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