Home Grown Botanical Acaricides: A One Health Strategy to Prevent Tick-Borne Diseases
Bibliographic record
Abstract
The prevalence of tick-borne zoonotic disease in Ontario, Canada, has steadily increased over the years. Global climate change has exacerbated the geographical spread, activity level, and population abundance of disease-causing ticks, resulting in the increased circulation of tick-borne disease and significant adverse health impacts on humans, non-human animals, and the environment. Given that existing initiatives demonstrate subpar efficacy and longevity, low accessibility and feasibility, or pose threats to non-human animal and environmental health, it is evident a One Health approach is needed to address this issue. This paper proposes a cost-effective home gardening guide that could be utilized to create botanical acaricides that have been proven to deter ticks. The solution, which employs the process of steam distillation to create essential oils from plants, uses Kingston, Ontario, Canada, as an example and places emphasis on the health and well-being of the environment, wild and domesticated non-human animals, and humans simultaneously.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".