Bibliographic record
Abstract
Wine is a complex beverage, comprising thousands of metabolites that are produced through the action of a plethora of yeasts and bacteria during fermentation of grape must. These microbial communities originate in the vineyard and the winery and reflect the influence of several factors including grape variety, geographical location, climate, vineyard spraying, technological practices, processing stage and season (pre-harvest, harvest, post-harvest). Vineyard and winery microbial communities have the potential to participate during fermentation and influence wine flavour and aroma. Therefore, there is an enormous interest in isolating and characterising these communities, particularly non-Saccharomyces yeast species to increase wine flavour diversity, while also exploting regional signature microbial populations to enhance regionality. In this review we describe the role and relevance of the main non-Saccharomyces yeast species found in vineyards and wineries. This includes the latest reports covering the application of these species for winemaking; and the biotechnological characteristics and potential applications of non-Saccharomyces species in other areas. In particular, we focus attention on the species for which molecular and genomic tools and resources are available for study. Copyright © 2016 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".