A Conceptual Model for the Impact of Climate Change on Fox Rabies in Alaska, 1980–2010
Bibliographic record
Abstract
The direct and interactive effects of climate change on host species and infectious disease dynamics are likely to initially manifest\ at latitudinal extremes. As such, Alaska represents a region in the United States for introspection on climate change and disease. Rabies is enzootic among arctic foxes (Vulpes lagopus) throughout the northern polar region. In Alaska, arctic and red foxes (Vulpes vulpes) are reservoirs for rabies, with most domestic animal and wildlife cases reported from northern and western coastal Alaska. Based on passive surveillance, a pronounced seasonal trend in rabid foxes occurs in Alaska, with a peak in winter and spring. This study describes climatic factors that may be associated with reported cyclic rabies occurrence. Based upon probabilistic modelling, a stronger seasonal effect in reported fox rabies cases appears at higher latitudes in Alaska, and rabies in arctic foxes appear disproportionately affected by climatic factors in comparison with red foxes. As temperatures continue a warming trend, a decrease in reported rabid arctic foxes may be expected. The overall epidemiology of rabies in Alaska is likely to shift to increased viral transmission among red foxes as the primary reservoir in the region. Information on fox and lemming demographics, in addition to enhanced rabies surveillance among foxes at finer geographic scales, will be critical to develop more comprehensive models for rabies virus transmission in the region.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".