Outbreak investigations of <i>Salmonella</i> and frozen raw breaded chicken: the mitigation of a significant public health issue in Canada
Bibliographic record
Abstract
Abstract In May 2017, whole-genome sequencing (WGS) became the primary subtyping method for Salmonella in Canada. As a result of the increased discriminatory power provided by WGS, 16 multi-jurisdictional outbreaks of Salmonella associated with frozen raw breaded chicken products were identified between 2017 and 2019. The majority (15/16) were associated with S. enteritidis , while the remaining outbreak was associated with S. Heidelberg. The 16 outbreaks included a total of 487 cases with ages ranging from 0 to 98 years (median: 24 years); 79 hospitalizations and two deaths were reported. Over the course of the outbreak investigations, 14 frozen raw breaded chicken products were recalled, and one was voluntarily withdrawn from the market. After previous changes to labelling and the issuance of public communication for these products proved ineffective at reducing illnesses, new industry requirements were issued in 2019, which required the implementation of measures at the manufacturing/processing level to reduce Salmonella to below detectable amounts in frozen raw breaded chicken products. Since implementation, no further outbreaks of Salmonella associated with frozen breaded chicken have been identified in Canada, a testament to the effectiveness of these risk mitigation measures.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".