A 4-year study of avian influenza virus prevalence and subtype diversity in ducks of Newfoundland, Canada
Bibliographic record
Abstract
The island of Newfoundland, Canada, is at the eastern edge of North America and has migratory bird connections with the continental mainland as well as across the North Atlantic Ocean. Here, we report a 4-year avian influenza virus (AIV) epidemiological study in ducks in the St. John's region of Newfoundland. The overall prevalence of AIV detection in ducks during this study was 7.2%, with American Black Ducks contributing the vast majority of the collected samples and the AIV positives. The juvenile ducks showed a significantly higher AIV detection rate (10.6%) compared with adults (3.4%). Seasonally, AIV prevalence rates were higher in the autumn (8.4%), but positives were still detected in the winter (4.6%). Preliminary serology tests showed a high incidence of previous AIV infection (20/38, 52.6%). A total of 43 viruses were characterized for their HA-NA or HA subtypes, which revealed a large diversity of AIV subtypes and little recurrence of subtypes from year to year. Investigation of the movement patterns of ducks in this region showed that it is a largely non-migratory duck population, which may contribute to the observed pattern of high AIV subtype turnover. Phylogenetic analysis of 4 H1N1 and one H5N4 AIVs showed these viruses were highly similar to other low pathogenic AIV sequences from waterfowl in North America and assigned all gene segments into American-avian clades. Notably, the H1N1 viruses, which were identified in consecutive years, possessed homologous genomes. Such detection of homologous AIV genomes across years is rare, but indicates the role of the environmental reservoir in viral perpetuation.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| 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".