Flavi and Bunyavirus mosquito vector distribution in North Western Canada
Bibliographic record
Abstract
Background: Arthropod borne virus have gained increasing attention over the last decade. Their distribution is believed to be highly affected by climate change due to the associated changes in vector ecology. The rapid spread of West Nile virus over the last decade has confirmed the importance of monitoring arthropod borne pathogens. The introduction of exotic animal and human disease vectors to Canada could pose signifcant animal and human health risks. In this project, we investigate the distribution of potential Flavi- and Bunyavirus vectors in selected areas of northern Alberta and the southern Northwest Territories. Methods: Mosquitoes were collected in eight locations of northern Alberta (AB) and the southern Northwest Territories (NWT) in the vector season of 2010 (AB) and 2008 – 2010 (NWT). Mosquitoes were sorted to species and pooled by sampling date, location and species. RNA was extracted from pools and tested for the presence of West Nile virus (Flavivirus), and Bunyamwera virus specific RNA by real time RT-PCR and qualitative RT-PCR. Results: Culex tarsalis, the main transmitting vector of West Nile Virus in Western Canada, was found as far north as Yellowknife, NWT in 2010. These findings were consistent over two years. No Culex tarsalis weres found in the other regions that were sampled. Similarly, Aedes vexans was found in the Chinchaga, but none of the other sampling regions. Culiseta inornata, one of the main transmitting vectors for northern Bunyaviruses (Cache Valley virus, Snowshoe Hare virus, Jamestown Canyon virus), was consistently found in most of the sampling locations. No Flavivirus specific RNA was detected in the tested samples. Conclusion: The presence of Culex tarsalis as far north as Yellowknife indicates the need for systematic surveillance of arthropod vectors because although no virus was detected in the samples collected in the years of the project further sampling is required to be certain, and predictive models for other pathogens have demonstrated that changing climatic variables have the potential to favour the spread of competent vectors and pathogens further north.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".