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Record W2748144003 · doi:10.5539/jfr.v6n5p59

Deterioration of Extra Virgin Olive Oil Caused by Different Processes

2017· article· en· W2748144003 on OpenAlexvenueno aff
Nadia Segura, Yenny Pinchak, Natalie Merlinski, Miguel Amarillo, Camila Feller, Bruno Irigaray, Laura Raggio, Mariana Orono, Marı́a A. Grompone

Bibliographic record

VenueJournal of Food Research · 2017
Typearticle
Languageen
FieldChemistry
TopicEdible Oils Quality and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsPhenolsFood sciencePolyphenolOlive oilChemistryAntioxidantComposition (language)Antioxidant capacityOrganic chemistryArt

Abstract

fetched live from OpenAlex

Extra virgin olive oil is recognized as a very stable oil because of its composition in fatty acids and its content in natural antioxidants (tocopherols and polyphenols). In the bibliography are works that address different aspects of this stability, from the duration of its useful life to its performance in the frying of foods. Some works also link their stability with the content of natural antioxidants. For example, Franco et al. (2014) studied the content of phenols and their antioxidant capacity in olive oils of seven different varieties. Baccouri et al. (2008) found a good correlation between the oxidative stability (measured in Rancimat) of the oils studied and the concentration of total phenols and tocopherols.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.008
Threshold uncertainty score0.308

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.000
Research integrity0.0000.001
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 head0.147
GPT teacher head0.413
Teacher spread0.266 · 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.

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

Citations4
Published2017
Admission routes1
Has abstractyes

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