Phylogenetic Inference of H3N2 Canine Influenza A Outbreak in Ontario, Canada in 2018
Bibliographic record
Abstract
The first Canadian H3N2 canine influenza A outbreak involving an Asian-origin H3N2 canine influenza virus (CIV) began in southwestern Ontario, Canada, in late December 2017. More H3N2 CIV cases were identified in central and eastern Ontario between March and October 2018. Based on epidemiological investigation, 5 clusters were identified (C1, C2, C3a, C3b, and C4); however, the origin of infection has only been revealed for epidemiological cluster C1. Here, we use phylogenetic analyses to unravel the links of virus transmission between the 5 epidemiological clusters and the origin of infection for all epidemiological clusters. Our results demonstrate that the Canadian H3N2 CIV sequences were grouped into four distinct phylogenetic clusters with minimal genetic diversity between these clusters. Large scale phylogenetic analysis of H3N2 CIV from around the globe showed that the Canadian CIVs formed a distinct new clade along with CIVs that have been circulating in the USA since 2017-2018 and in China since 2017. This clade shares a common ancestor of Asian origin. This study concludes that the H3N2 CIV outbreak in Ontario was driven by multiple introductions of South Korean/Chinese-origin H3N2 CIVs over 10 months.
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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 | 0.004 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".