Assessing the Role of Seabirds in the Ecology of Influenza A Viruses
Bibliographic record
Abstract
Wild waterbirds, specifically waterfowl, gulls, and shorebirds, are recognized as the primordial reservoir of influenza A viruses (IAVs). However, the role of seabirds, an abundant, diverse, and globally distributed group of birds, in the perpetuation and transmission of IAVs is less clear. Here we summarize published and publicly available data for influenza viruses in seabirds, which for the purposes of this study are defined as birds that exhibit a largely or exclusively pelagic lifestyle and exclude waterfowl, gulls, and shorebirds, and we review this collective dataset to assess the role of seabirds in the influenza A ecology. Since 1961, more than 40,000 samples have been collected worldwide from the seabirds considered here and screened, using a variety of techniques, for evidence of active or past IAV infection. From these data, the overall prevalence of active infection has been estimated to be very low; however, serological data provide evidence that some seabird species are more frequently exposed to IAVs. Sequence data for viruses from seabirds are limited, except for murres (common murre, Uria aalge, and thick-billed murre, Uria lomvia; family Alcidae) for which there are full or partial genome sequences available for more than 80 viruses. Characterization of these viruses suggests that murres are infected with Group 1 hemagglutinin subtype viruses more frequently as compared to Group 2 and also indicates that these northern, circumpolar birds are frequently infected by intercontinental reassortant viruses. Greater temporal and spatial sampling and characterization of additional viruses are required to better understand the role of seabirds in global IAV dynamics.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".