The Analysis of eTick Submission in Ontario
Bibliographic record
Abstract
Purpose: Ixodes scapularis, also known as the eastern blacklegged tick, is associated with the vector-borne Lyme disease in North America. With climate change, warming temperatures have increased the number of areas suitable for ticks, and contributed to the expansion of tick species in Canada. The purpose of this project was to identify recent trends in tick range expansion and species diversity in Ontario by analyzing 2019 to 2022 data from the web-based tick surveillance platform, eTick.ca. Method: The eTick.ca web platform allows the public to submit tick photos for identification. We extracted data from the tick submissions for Ontario between mid-2019 to 2022 including information on the type of species, host types, travel history, and location. Microsoft Excel was used to generate distribution tables and graphs of tick submissions by species, month/year and host type for Ontario. Geographic Information Systems (ArcGIS) and SaTScan software were used to identify spatial clusters of tick submissions adjusting for the human population size using Ontario census subdivisions. Result: A total of 14,611 tick photo submissions were recorded between 2020 to 2022, excluding those with a history of recent travel. The year 2021 had the highest number of submissions (n=7339). Dermacentor species comprised the majority of submissions (n=9498, 65%), followed by I. scapularis (n=4810, 33%) and other species (n=303, 2%) between 2020-2022. Ticks were most commonly discovered on a human host (n=10,084), followed by animal hosts (n=3485), and free in environments (n=1042). Additionally, the majority of species were found in the adult stage (n=12,821, 88%), followed by unknown (n=1539, 10%) and immature stages (n=251, 2%). Clusters of I. scapularis were present in the Eastern, Central, and Southern Ontario regions, while clusters of Dermacentor sp. were present in Southern and Central Ontario regions. Conclusion: Spatial and temporal variations in tick submissions in Ontario were identified over the 3.5 year period since the implementation of eTick in the province. Data from eTick can be used to identify hotspots of human-tick exposure.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| 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) | 0.004 | 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".