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Record W7132986143

Quantifying food quality:The case of alkyl-methoxypyrazines in wine

2016· article· en· W7132986143 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

VenueCharles Sturt University Research Output (CRO) · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFermentation and Sensory Analysis
Canadian institutionsBrock University
Fundersnot available
KeywordsWineMass spectrometryAroma of wineSolid-phase microextractionGas chromatography–mass spectrometryTRACE (psycholinguistics)OrganolepticGas chromatography
DOInot available

Abstract

fetched live from OpenAlex

Wine is the oldest alcoholic beverage, and the most commonly consumed in many countries, including France, Sweden, Italy and Argentina. Its sensory quality is dependent on the relative prevalence of the 200+ odorants known to influence wine flavor. Many of these odor-active compounds exist at trace concentrations, yet still exhibit potent effects due to their low detection thresholds in humans. An important example is 3-alkyl-2-methoxypyrazines (MPs), which are capable of tainting both grape juice and wine, yet possess sensory thresholds well below the sensitivity of established analytical methods. Here we describe the development of a method based on multi dimensional gas chromatography coupled with mass spectrometry and headspace solid phase microextraction (SPME-MDGCMS) that allows for the measurement of MPs in wine down to the low ng/L range.

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)0.001
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 score0.615
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.000

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 head0.281
GPT teacher head0.372
Teacher spread0.091 · 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