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.
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.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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 it