Longitudinal Influenza A Virus Screening of Retail Milk from Canadian Provinces (Rolling Updates)
Bibliographic record
Abstract
Abstract Highly pathogenic avian influenza (HPAI) H5N1 has caused the deaths of more than 100 million birds since 2021, and human cases since 1997 have been associated with significant morbidity and mortality. Given the recent detection of HPAI H5N1 in dairy cattle and H5N1 RNA detections in pasteurized retail milk in the United States, we established the Pan-Canadian Milk (PCM) Network. Through our network of collaborators from across Canada, retail milk is being procured longitudinally and sent to a central laboratory for testing for the presence of influenza A virus RNA. To date (05 July 2024), we have tested 92 retail milk samples from all ten Canadian provinces (NL, NS, PEI, NB, QC, ON, MB, SK, AB, and BC) and all have tested negative for influenza A virus RNA. Testing is ongoing and these results will be updated on rolling basis as additional data becomes available. Despite no known HPAI infections of dairy cattle in Canada to date, H5N1 poses a significant threat to the health of both humans and other animals. Routine surveillance of retail milk on a national scale will allow for monitoring of infected dairy cattle on an ongoing basis in a cost-effective, standardized, scalable and easily accessible manner. Our network and testing will act as an early detection system to help inform containment and mitigation activities if positive samples are identified.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".