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Record W1999402120 · doi:10.1007/s11746-015-2612-9

Oxidation Rates of Triacylglycerol and Ethyl Ester Fish Oils

2015· article· en· W1999402120 on OpenAlexaff
Jenna C. Sullivan Ritter, Suzanne M. Budge, Fabiola Jovica, Anna‐Jean Reid

Bibliographic record

VenueJournal of the American Oil Chemists Society · 2015
Typearticle
Languageen
FieldChemistry
TopicEdible Oils Quality and Analysis
Canadian institutionsDalhousie University
Fundersnot available
KeywordsChemistryArrhenius equationReaction rate constantKineticsFish oilLipid oxidationFish <Actinopterygii>Activation energyPeroxide valueReaction rateOrganic chemistryNuclear chemistryAntioxidantCatalysisBiology

Abstract

fetched live from OpenAlex

Abstract Fish oil is available primarily as triacylglycerols (TAG) or ethyl esters (EE). Anecdotal evidence suggests that TAG have superior bioavailability and oxidative stability compared to EE. In this work, peroxide value (PV) and p‐anisidine value (AV) were used to monitor oxidation in commercially available TAG and EE fish oils incubated at temperatures from 5 to 60 °C. Pseudo first‐order kinetics were assumed and rate constants were calculated for each temperature. At all temperatures, the rates of oxidation were higher for EE oils than TAG oils. For PV and AV measured in both oils, non‐linear Arrhenius models were plotted, generating activation energies that ranged from 7 to 103 and 2 to 159 kJ/mol for PV and AV, respectively. Although TAG were more resistant to oxidation than EE, they had lower activation energies (Ea) at ≤15 °C for reactions measured with PV and AV. The Ea for EE was negative at temperatures ≥45 °C, indicating that reaction rate was influenced by factors in addition to temperature.

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)0.001
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.035
GPT teacher head0.306
Teacher spread0.271 · 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

Citations25
Published2015
Admission routes1
Has abstractyes

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