<i>Listeria monocytogenes</i>cross-contamination of cheese: risk throughout the food supply chain
Bibliographic record
Abstract
Listeria monocytogenes has been the most common microbial cause of cheese-related recalls in both the United States and Canada in recent years. Since L. monocytogenes is inactivated by pasteurization, the majority of these cases have been linked to environmental and cross-contamination of fresh-soft, soft-ripened, and semi-soft cheeses. Cross-contamination of foods with L. monocytogenes is a continuous risk throughout the food supply chain and presents unique challenges for subsequent illness and outbreak investigations. Reports on outbreaks of listeriosis attributed to cross-contamination downstream from primary processing help highlight the critical role of epidemiological investigation coupled with coordinated molecular subtyping and surveillance in the recognition and investigation of complex foodborne outbreaks. Despite their complexity, environmental sampling throughout the supply chain coupled with improved genotyping approaches and concomitant analysis of foodborne illness epidemiological exposure data are needed to help resolve these and similar cases more rapidly and with greater confidence.
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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 | 0.002 | 0.001 |
| 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".