Characterization of microorganisms following dairy keeping quality tests in Québec
Bibliographic record
Abstract
: Despite best efforts of the dairy industry, premature spoiling and non-compliance of products remain problematic and cause economic loss. In this study, 190 dairy products/samples of the Québec province were analyzed using governmental quality tests and keeping quality tests, such as the Virginia Tech. procedure, the Moseley test and a Paenibacillus test, to allow identification, by 16S sequencing, and characterization of the microorganisms causing non-compliance. We found that the Paenibacillus test isolated mostly Bacillus and Paenibacillus whereas the other tests isolated primarily Pseudomonas . Tests in 96-well assay plates showed that Pseudomonas had the most moderate to strong biofilm forming ability producers. Except for four isolates of Pseudomonas and one isolate of Stenotrophomonas chelatiphaga , biofilm producers were sensitive to both sodium hypochlorite and peracetic acid at concentrations typically used to disinfect dairy equipment. This study will help in the development of control strategies targeting problematic bacterial contaminants in the dairy sector.
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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".