Migration strategy affects avian influenza dynamics in mallards (<i><scp>A</scp>nas platyrhynchos</i>)
Bibliographic record
Abstract
Studies of pathogen transmission typically overlook that wildlife hosts can include both migrant and resident populations when attempting to model circulation. Through the application of stable isotopes in flight feathers, we estimated the migration strategy of mallards (Anas platyrhynchos) occurring on California wintering grounds. Our study demonstrates that mallards- a principal host of avian influenza virus (AIV) in nature, contribute differently to virus gene flow depending on migration strategy. No difference in AIV prevalence was detected between resident (9.6%), intermediate-distance (9.6%) and long-distance migrants (7.4%). Viral diversity among the three groups was also comparable, possibly owing to viral pool mixing when birds converge at wetlands during winter. However, migrants and residents contributed differently to the virus gene pool at wintering wetlands. Migrants introduced virus from northern breeding grounds (Alaska and the NW Pacific Rim) into the wintering population, facilitating gene flow at continental scales, but circulation of imported virus appeared to be limited. In contrast, resident mallards acted as AIV reservoirs facilitating year-round circulation of limited subtypes (i.e. H5N2) at lower latitudes. This study supports a model of virus exchange in temperate regions driven by the convergence of wild birds with separate geographic origins and exposure histories.
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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".