Comprehensive Risk Pathway of the Qualitative Likelihood of Human Exposure to Severe Acute Respiratory Syndrome Coronavirus 2 from the Food Chain
Bibliographic record
Abstract
ABSTRACT: A group of experts from all Canadian federal food safety partners was formed to monitor the potential issues relating to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) food contamination, to gather and consider all of the relevant evidence and to determine the impact for Canadian food safety. A comprehensive risk pathway was generated to consider the likelihood of a SARS-CoV-2 contamination event at any of the relevant steps of the food processing and handling chain and the potential for exposure and transmission of the virus to the consumer. The scientific evidence was reviewed and assessed for each event in the pathway, taking into consideration relevant elements that could increase or mitigate the risk of contamination. The advantage of having an event-wise contextualization of the SARS-CoV-2 transmission pathway through the food chain is that it provides a systematic and consistent approach to evaluate any new data and communicate its importance and impact. The pathway also increases the objectivity and consistency of the assessment in a rapidly evolving and high-stakes situation. Based on our review and analysis, there is currently no comprehensive epidemiological evidence of confirmed cases of SARS-CoV-2, or its known variants, causing coronavirus disease 2019 from transmission through food or food packaging. Considering the remote possibility of exposure through food, the likelihood of exposure by ingestion or contact with mucosa is considered negligible to very low, and good hygiene practices during food preparation should continue to be followed.
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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 | 0.027 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.013 | 0.008 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".