Quality of Cabernet Sauvignon Wines Determined by the Variability of Climatic Attributes
Bibliographic record
Abstract
Essential to understand the dynamics responsible for the quality of red wines, the objective of revealing the physico-chemical and climatologic relationships that determine the quality of Cabernet Sauvignon wines. The experiment was carried out in the municipality of Dom Pedrito, Rio Grande do Sul, Brazil, in the agricultural crop of 2016. The experiment was conducted in a randomized block design where the treatments corresponded to nine microvinifications arranged in three replicates. The concentration of total polyphenols in Cabernet Sauvignon red wines is associated with anthocyanins, indices of absorbances of 420 and 520, as well as total acidity. However, the tannins are directly proportional to the total acidity of the wine. Environmental conditions with high rainfall, minimum oscillations in thermal amplitude and incident solar radiation tend to increase the hydrogenionic potential and the absorbance indices of 420 (yellow) and 620 (bluish) red wines of Cabernet Sauvignon. The thermal amplitude was preponderant to elevate levels of anthocyanins in Cabernet Sauvignon wines.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 teacher head, 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".