contains supplementary material, which is available to authorized users.
Bibliographic record
Abstract
# The Author(s) 2012. This article is published with open access at Springerlink.com Abstract The cheese microbial ecosystem is complex, and the presence of non-starter adventitious microorganisms in milk may have an influence on the organoleptic characteristics of cheese. The aim of this study was to analyze the composition and diversity of the fungal flora of raw milk destined for cheesemaking from 19 dairy farms in Quebec and to monitor their evolution throughout ripening. Six hundred ten yeast and mold isolates were collected from raw milk and raw milk cheeses over a 9-month period. Based on the sequences of the rDNA ITS1-5.8S-ITS2 region, 67 % of the raw milk isolates were yeasts, which were assigned to 37 species across 11 genera, while 33 % were molds, which were assigned to 33 species across 25 genera. A semi-quantitative analysis of the yeasts and molds in the raw milk from four farms was performed over a 5-month period. The composition and diversity of the fungal microflora were totally different for each farm, each of which had a unique species profile. To determine whether adventitious yeast strains from the milk could develop in raw milk cheese, a
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.909 | 0.778 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".