Risks and new challenges in the food chain: Viral contamination and decontamination from a global perspective, guidelines, and cleaning
Bibliographic record
Abstract
Even during the continuing world pandemic of severe acute respiratory syndrome coronavirus 2 (SARS CoV-2), consumers remain exposed to the risk of getting infected by existing, emerging, or re-emerging foodborne and waterborne viruses. SARS-CoV-2 is different in that it is transmitted directly via the airborne route (droplets and aerosols) or indirect contact (surfaces contaminated with SARS-CoV-2). International food and health organizations and national regulatory bodies have provided guidance to protect individuals active in food premises from potential occupational exposure to SARS-CoV-2, and have recommended chemicals effective in controlling the virus. Additionally, to exclude transmission of foodborne and waterborne viruses, hygiene practices to remove viral contaminants from surfaces are applied in different stages of the food chain (e.g., food plants, food distribution, storage, retail sector, etc.), while new and enhanced measures effective in the control of all types of viruses are under development. This comprehensive review aims to analyze and compare efficacies of existing cleaning practices currently used in the food industry to remove pathogenic viruses from air, nonfood, and food contact surfaces, as well as from food surfaces. In addition, the classification, modes of transmission, and survival of food and waterborne viruses, as well as SARS-CoV-2 will be presented. The international guidelines and national regulations are summarized in terms of virucidal chemical agents and their applications.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".