Highly pathogenic avian influenza: Unprecedented outbreaks in Canadian wildlife and domestic poultry
Bibliographic record
Abstract
Canada experienced a wave of HPAI H5N1 outbreaks in the spring of 2022 with millions of wild and farmed birds being infected. Seabird mortalities in Canada have been particularly severe on the Atlantic Coast over the summer of 2022. Over 7 million birds have been culled in Canada, and outbreaks continue to profoundly affect commercial bird farms across the world. This new H5N1 virus can and has infected multiple mammalian species, including skunks, foxes, bears, mink, seals, porpoises, sea lions, and dolphins. Viruses with mammalian adaptations such as the mutations PB2-E627K, E627V, and D701N were found in the brain of various carnivores in Europe and Canada. To date this specific clade of H5N1 virus has been identified in less than 10 humans. At the ground level, awareness should be raised among frontline practitioners most likely to encounter patients with HPAI.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".