DEMOGRAPHIC AND ENVIRONMENTAL FACTORS ASSOCIATED WITH BAYLISASCARIS PROCYONIS INFECTION OF RACCOONS (PROCYON LOTOR) IN ONTARIO, CANADA
Bibliographic record
Abstract
The raccoon (Procyon lotor) roundworm, Baylisascaris procyonis, is an emerging wildlife zoonosis of public health significance in North America. Although the adult stage typically causes no disease in raccoons, the larval stage can cause significant disease in a variety of species, including humans. Raccoons often use human environments, which may increase the risk of B. procyonis exposure in people, particularly in urban settings. Because of this, our objectives were to identify host and environmental risk factors associated with the prevalence and intensity of B. procyonis infection in raccoons in Ontario, Canada. Between 2013 and 2016, 1,539 raccoons were collected and examined for the presence of B. procyonis. Thereafter, we analyzed our data for the influence of age, sex, fat stores, human population size, land use classification, season, and year of collection on the prevalence and intensity of infection. With multilevel logistic regression models, we identified significant associations between prevalence and host age, prevalence and amount of fat stores, and prevalence and season of collection; a significant two-way interaction was also identified between host sex and land use classification. Additionally, by using multilevel negative binomial regression models, we identified significant associations between the intensity of parasite infection and season of collection, as well as three significant two-way interactions: host sex and land use classification, host age and land use classification, and host sex and amount of fat stores. These findings help provide a more complete understanding of B. procyonis ecology in raccoons, including identifying associations between different environments and B. procyonis, which may assist in the development of future risk management strategies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".