A Case-study on the Selection of Promising Functional Starter Strains from Grape Yeasts: A Report by Student of Food Science and Technology Degree, University of Foggia (Southern Italy)
Bibliographic record
Abstract
The main aim of this research, performed by some students in Food Science and Technology of Foggia University, is to show how perform the selection of a functional starter through a step-by-step procedure. Fifteen yeast strains were studied in order to assess their biotechnological traits, e.g. catalase, urease, B-glucosidase, pectolytic and xylanolytic activities, production of H2S, resistance to copper, SO2 and acetic acid, growth at different temperatures, alkaline pH, in presence of different amounts of ethanol and glucose, and some probiotic properties. After studying these abilities, yeasts were identified through the miniaturized system API 20 C AUX and two kinds of multivariate analyses (Cluster Analysis and Principal Component Analysis) were performed to highlight the best strains.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".