Chemometric analysis of gas chromatographic data—investigation of enological parameters of a bag‐in‐box white wine as affected by storage time and temperature
Bibliographic record
Abstract
In this study, a bag‐in‐box white wine was stored at 22, 35, and 45 °C for up to 48 days to produce a series of samples that exhibited different enological parameters (absorbance at 420 nm, free SO2, total SO2, total phenol, and total aldehyde). Wine samples were extracted with dichloromethane and analyzed using gas chromatography (GC) to generate volatile fingerprints. Principal component analysis (PCA) score plots of the first three principal components showed grouping trends that were influenced by storage time and temperature. PCA loading plots revealed that changes in chemical profiles were different for wines held at different storage temperatures. Storage time could be predicted accurately by partial least squares (PLS) regression of the GC data. Coefficients of determination (R2) were >0.99, and the standard error of prediction values were 0.4, 0.5, and 1.9 days over the test period of 15, 30, and 48 days, respectively. Using the same GC data with PLS analyses, the enological parameters could be accurately predicted from GC fingerprints, except for the predictions of SO2 in a wine stored at 22 °C and total phenol in a wine stored at 45 °C. Copyright © 2011 John Wiley & Sons, Ltd.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".