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Record W3207511967 · doi:10.3390/separations8100173

Tyrosol and Hydroxytyrosol Determination in Extra Virgin Olive Oil with Direct Liquid Electron Ionization-Tandem Mass Spectrometry

2021· article· en· W3207511967 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSeparations · 2021
Typearticle
Languageen
FieldChemistry
TopicEdible Oils Quality and Analysis
Canadian institutionsVancouver Island University
Fundersnot available
KeywordsHydroxytyrosolTyrosolChemistryRepeatabilityChromatographySample preparationMass spectrometryLiquid chromatography–mass spectrometryOlive oilIonizationTandem mass spectrometryAnalytical Chemistry (journal)PolyphenolOrganic chemistryFood scienceAntioxidant

Abstract

fetched live from OpenAlex

Extra virgin olive oil (EVOO) is one of the main ingredients of the Mediterranean diet. It is claimed as a functional food for its unique content of health-promoting compounds. Tyrosol (Tyr), Hydroxytyrosol (Htyr), and their phenolic derivatives present in EVOO show beneficial properties, and their identification and quantification, both in their free form and after the hydrolysis of more complex precursors, are important to certify its quality. An alternative method for quantifying free and total Tyr and Htyr in EVOO is presented using an LC–MS interface based on electron ionization (EI), called liquid electron ionization (LEI). This method requires neither sample preparation nor chromatography; the sample is diluted and injected. The selectivity and sensitivity were assessed in multiple reaction monitoring mode (MRM), obtaining confirmation and quantification in actual samples ranging from 5 to 11 mg/Kg for the free forms and from 32 to 80 mg/Kg for their total amount after hydrolysis. Two MS/MS transitions were acquired for both compounds using the Q/q ratios as confirmatory parameters. Standard addition calibration curves demonstrated optimal linearity and negligible matrix effects, allowing a correct quantification even without expensive and difficult to find labeled internal standards. After several weeks of operation, the system’s repeatability was excellent, with an intraday RSD (%) spanning from five to nine and an interday RSD (%) spanning from 9 to 11.

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.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.043
Threshold uncertainty score0.669

Codex and Gemma teacher scores by category

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

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 head0.010
GPT teacher head0.262
Teacher spread0.252 · 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