Distribution of Ixodes scapularis in Northwestern Ontario: Results from Active and Passive Surveillance Activities in the Northwestern Health Unit Catchment Area
Bibliographic record
Abstract
The range of Ixodes scapularis is expanding in Ontario, increasing the risk of Lyme disease. As an effective public health response requires accurate information on disease distribution and areas of risk, this study aims to establish the geographic distribution of I. scapularis and its associated pathogen, B. burgdorferi, in northwestern Ontario. We assessed five years of active and passive tick surveillance data in northwestern Ontario. Between 2013 and 2017, 251 I. scapularis were submitted through passive surveillance. The submission rate increased over time, and the proportion infected with B. burgdorferi was 13.5%. Active tick surveillance from 2014 to 2016 found few I. scapularis specimens. In 2017, 102 I. scapularis were found in 10 locations around the city of Kenora; 60% were infected with B. burgdorferi, eight tested positive for A. phagocytophilum, and one for POWV. I. scapularis ticks were found in 14 locations within the Northwestern Health Unit area, with seven locations containing B. burgdorferi-positive ticks. We found abundant I. scapularis populations in the southern portion of northwestern Ontario and northward expansion is expected. It is recommended that I. scapularis populations continue to be monitored and mitigation strategies should be established for rural northern communities.
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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 | 0.001 |
| 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) | 0.001 | 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".