Molecular Identification and Distribution of Yeasts in Fruits
Bibliographic record
Abstract
Yeasts are common microbes in both natural and artificial environments. They play significant roles in the food industry, environment, and human health. Due to easy access for microbes to the simple sugars in fruits, including yeasts, fruits could be a significant source of yeasts that could impact both the quality of food as well as human health. In this chapter, we review our current understanding of yeasts in both fresh and processed fruits. We concentrate our efforts on studies that have used molecular methods for yeast species and genotype identifications. While a variety of methods have been used, sequencing of the ITS region has become the standard for yeast species identification and new species discovery. A wide variety of yeast species have been found in fruits and many factors such as fruit type, fruit variety, fruit maturation time, the degree of fruit processing, and the location and climate of fruit growth and processing have been shown to influence yeast species composition associated with fruits. However, many fruits still remain to be investigated for their yeast communities and the mechanisms that govern yeast species and genotype distribution in fruits are largely unknown at present.
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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 | 0.000 | 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) | 0.000 | 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".