The Role of Urban-to-Rural Gradients in Mosquito-Borne Disease Risk in Ontario, Canada
Bibliographic record
Abstract
In North America, the risk of mosquito-borne disease is thought to be shifting because of human development, with notable differences in disease risk between urban, rural, and natural ecosystems.In Eastern Ontario, I highlight differences in West Nile virus (WNV) and eastern equine encephalitis virus (EEEV) transmission risk to wildlife and exposure risk for Song Sparrows across urban-to-rural gradients.I found changes in mosquito host use between urban and rural environments, with potential mammal-based circulation of WNV occurring alongside a typical cycle between birds and mosquitoes.Additionally, I found significant differences in WNV and EEEV seroprevalence between Song Sparrows (Melospiza melodia) from urban, rural, and forested areas, with less WNV prevalence in forested areas and more EEEV prevalence in forested or urban habitats.I recommend continuing surveillance in mosquitoes and wildlife across urban and rural landscapes to better predict mosquito-borne disease outbreak potential.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".