California Serogroup Viruses in a Changing Canadian Arctic: A Review
Bibliographic record
Abstract
The Arctic is warming at four times the global rate, changing the diversity, activity and distribution of vectors and associated pathogens. While the Arctic is not often considered a hotbed of vector-borne diseases, Jamestown Canyon virus (JCV) and Snowshoe Hare virus (SSHV) are mosquito-borne zoonotic viruses of the California serogroup endemic to the Canadian North. The viruses are maintained by transovarial transmission in vectors and circulate among vertebrate hosts, both of which are not well characterized in Arctic regions. While most human infections are subclinical or mild, serious cases occur, and both JCV and SSHV have recently been identified as leading causes of arbovirus-associated neurological diseases in North America. Consequently, both viruses are currently recognised as neglected and emerging viruses of public health concern. This review aims to summarise previous findings in the region regarding the enzootic transmission cycle of both viruses. We identify key gaps and approaches needed to critically evaluate, detect, and model the effects of climate change on these uniquely northern viruses. Based on limited data, we predict that (1) these northern adapted viruses will increase their range northwards, but not lose range at their southern limits, (2) undergo more rapid amplification and amplified transmission in endemic regions for longer vector-biting seasons, (3) take advantage of northward shifts of hosts and vectors, and (4) increase bite rates following an increase in the availability of breeding sites, along with phenological synchrony between the reproduction cycle of theorized reservoirs (such as caribou calving) and mosquito emergence.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".