West Nile virus and sage-grouse: What more have we learned?
Bibliographic record
Abstract
West Nile virus (WNv) has emerged as a new issue in the conservation of native avifauna in North America. Mortality associated with WNv infection decreased survival of female greater sage-grouse (Centrocercus urophasianus) by 25% across 4 populations in Wyoming and Montana, USA, and Alberta, Canada, in 2003. In 2004 WNv spread to populations in Colorado and California, and female survival in late summer was 10% lower at 4 sites with confirmed WNv mortalities (86% survival) than at 8 sites without (96%). We still have no evidence that sage-grouse show resistance to the virus. The 2004 WNv season was not the catastrophe that many had predicted, and the decrease in prevalence of infection and mortality in sage-grouse, humans, and horses (except in California) has left many wondering if the worst has past. Evidence suggests that risk of infection was low in 2004 because unseasonably cool summer temperatures delayed or reduced mosquito production. Moreover, mortalities occurred 2–3 weeks later in 2004 than in 2003, and the shift to later timing was consistent between years at sites where WNv reduced survival both years. Mosquito surveillance data indicated a sharp decline in prevalence and infection rate of adult C. tarsalis in southeast Alberta, the most northern latitude where WNv reduced survival, in 2003 but not in 2004. A full understanding of the implications of WNv for sage-grouse requires a long-term, coordinated monitoring strategy among researchers and a sensitivity analysis to evaluate the role of WNv in population viability. Epidemiological research examining the prevalence and ecology of the virus among reservoir hosts is crucial.
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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 | 0.008 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.006 | 0.014 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.010 | 0.009 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".