Microbial safety of cheese in Canada
Bibliographic record
Abstract
A profile of the microbial safety of cheese in Canada was established based on the analysis of 2955 pasteurized and raw-milk cheeses tested under Canada's National Microbiological Monitoring Program (NMMP) and 2009 raw-milk cheeses tested under the Targeted Survey Program. 97.8% of NMMP and 99.6% of Targeted Survey cheese samples were assessed as being of satisfactory microbiological safety. Under the NMMP, Salmonella spp. was detected in 2 samples, Listeria monocytogenes was detected in 15 samples and no Escherichia coli O157/H7:NM (non-motile) was detected. Cheese samples assessed as having unsatisfactory levels of S. aureus and generic E. coli were found in 18 and 41 samples, respectively. Under the Targeted Survey, L. monocytogenes was detected in 2 samples, while no Salmonella spp. or E. coli O157/H7:NM were detected. Cheese samples assessed as having investigative and unsatisfactory levels of S. aureus were found in 4 and 2 samples respectively. No samples were found to have investigative or unsatisfactory levels of generic E. coli. For cheese samples collected under the NMMP, logistic regression models indicated that contamination was more frequent in raw-milk cheeses compared to pasteurized-milk cheeses (OR = 5.0, 95% CI (3.0, 8.3)), and in imported cheeses compared to domestic cheeses (OR = 8.2, 95% CI (4.1, 16.1)). A statistically significant association was found between cheese samples assessed as having unsatisfactory levels of generic E. coli and detection of L. monocytogenes, Salmonella spp. or levels of S. aureus that were assessed as unsatisfactory (p < .001). These test results will help support risk analysis and inform food safety decisions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".