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Record W2101983700 · doi:10.5539/jfr.v2n1p31

A Case Study of Selected Volatile Phenols from Brettanomyces and Micronutrients Mn, Fe, Cu, Zn in Chianti Red Wines

2013· article· en· W2101983700 on OpenAlexvenueno aff
Gabriella Tamasi, Natalie F. Owens, Fabio Cascella, Marco Cerqua, Renzo Cini

Bibliographic record

VenueJournal of Food Research · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFermentation and Sensory Analysis
Canadian institutionsnot available
FundersUniversità degli Studi di SienaEmory University
KeywordsChemistryWinePhenolsManganeseAtomic absorption spectroscopyZincNuclear chemistrySolid phase extractionExtraction (chemistry)ChromatographyFood science

Abstract

fetched live from OpenAlex

Volatile phenols 4-Ethylphenol (EtP) and 4-Ethylguaiacol (EtG), and selected metals Mn, Fe, Cu, and Zn in Chianti red wines were determined via Head-Space Solid Phase Micro-Extraction pretreatment and Gas Chromatography-Mass Spectrometry and through Atomic Absorption Spectrophotometry. The wine samples were Chianti Classico DOCG (CdB) and Toscana IGT (CF) from seven vintages 2008-2003, 2001. The concentration for EtP was in the range 283-862 (CdB) and 155-643 ug L<sup>-1</sup> (CF), whereas the content of EtG ranged 40-116 (CdB) and 11-104 ug L<sup>-1</sup> (CF). The content for metals ranged 1.42-1.82, 0.93-4.68, <0.10-0.20, and 0.53-1.10 mg L<sup>-1</sup> for Mn, Fe, Cu, and Zn, respectively. The concentrations for EtP and EtG have high relative values for wines from 2004 and 2007 harvests. Interestingly, Manganese concentration follows a similar trend. Data about the metals and phenols are in agreement with much care at vine/grape and fermentation-aging-refinement procedures.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.815
Threshold uncertainty score0.403

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 head0.083
GPT teacher head0.319
Teacher spread0.236 · 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 designObservational
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

Citations7
Published2013
Admission routes1
Has abstractyes

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