Evaluation of Norovirus Persistence on Farm and Agriculturally-relevant Environments
Bibliographic record
Abstract
Human norovirus (NoV) causes gastroenteritis worldwide and has been associated with a number of produce related outbreaks. The design of effective inactivation and prevention procedures requires an understanding of virus survival in environments applicable to the production and processing of fresh produce. To evaluate the extent of NoV risk from farm to fork, the survival of murine norovirus (MNV), a surrogate for human NoV, was studied on stainless steel disks, soil and in bottled water for 42 days and on lettuce for 15 days in the laboratory. Stability experiments were then conducted on farm during one lettuce planting/harvest cycle, for 4 weeks. MNV stability was tested at room temperature in the laboratory or under ambient conditions on the farm. A one log reduction in virus titre was achieved after 30 days in water, 4 days on lettuce, 15 days on stainless steel disks, 12 days on loamy and sandy soil. For farm testing, infectious virus was recovered from both soil and lettuce on the day of inoculation. Although infectious virus was not recovered at later time points, the viral genomes were detected for up to four weeks. The observed long-term persistence of NoV, under both laboratory and field conditions, provides valuable information for developing risk assessments and control procedures to limit the possibility for NoV transmission in the food supply.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".