Assessing the Role of Seabirds in the Ecology of Influenza A Viruses
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it