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Microbial safety of cheese in Canada

2020· article· en· W3001065591 on OpenAlexaffabout
Kyle Ganz, Etsuko Yamamoto, Kate Hardie, Christine Hum, Hussein Hussein, Annie Locas, Marina Steele

Bibliographic record

VenueInternational Journal of Food Microbiology · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Safety and Hygiene
Canadian institutionsCanadian Food Inspection Agency
Fundersnot available
KeywordsPasteurizationSalmonellaListeria monocytogenesRaw milkFood scienceFood safetyContaminationBiologyListeriaEscherichia coliFood contaminantBacteria

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.490
Threshold uncertainty score0.964

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.014
GPT teacher head0.193
Teacher spread0.179 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations20
Published2020
Admission routes2
Has abstractyes

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