Prevalence of Foodborne Viruses in Berries Harvested in Canada
Bibliographic record
Abstract
It is known that the transmission of different foodborne viruses can occur either via discharge of contaminated water close to the production environment or via close contact with animal feces. Cranberries are intimately associated with water throughout their production cycle, and blueberries grow close to the ground which could lead to contact with wildlife. The aim of this study was to evaluate the prevalence of human norovirus (HuNoV GI and GII), hepatitis A virus (HAV) and hepatitis E virus (HEV) in two berries produced commercially in Canada. The detection of HuNoV and HAV on RTE cranberries and of HEV on wild blueberries was evaluated using the ISO method 15216-1:2017. Only 3 of 234 cranberry samples tested positive for HuNoV GI (3.6, 7.4, 5.3 genome copies/g, respectively) and all were negative for HuNoV GII and HAV. PMA pre-treatment and sequencing confirmed the absence of potential intact HuNoV GI particles on cranberries. None of the 150 blueberry samples tested positive for HEV. Overall, the prevalence of foodborne viruses in RTE cranberries and wild blueberries harvested in Canada is low, making these products relatively safe for consumers.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".