An updated inventory of mosquito species (Diptera: Culicidae) in Nova Scotia, Canada
Bibliographic record
Abstract
Abstract Shorter, warmer winters linked to climate change are inviting the northwards expansion of mosquito species (Diptera: Culicidae) and the pathogens they vector. Monitoring can play an important role in helping to mitigate the health impacts of mosquito-borne disease due to changes in regional mosquito species composition. To update the inventory of mosquito species currently residing in Nova Scotia, we sampled adult mosquitoes from 60 locations using Centers for Disease Control and Prevention light traps and collected mosquito larvae from 232 water sources across nine ecozones from May to October in 2021 and 2022. Of the 12 652 mosquitoes collected, we identified 35 species, including eight species not previously recorded in the province: Aedes aurifer (Coquillett) , Aedes decticus Howard et al ., Aedes pionips Dyar , Aedes hendersoni Cockerell, Aedes sticticus (Meigen) , Culiseta minnesotae Barr, Culiseta melanura (Coquillett), and Culex salinarius Coquillett. We have also observed the province-wide expansion of Aedes japonicus (Theobald) since the species’ first detection in Nova Scotia in 2007. Overall, vector species are being detected more frequently in Nova Scotia, highlighting potential changes in disease dynamics as climate change progresses and furthering the need for continued monitoring.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".