Bibliographic record
Abstract
Raccoons (Procyon lotor) are a successful urban adapter species that carry numerous pathogens of public health and veterinary significance. One such pathogen is the zoonotic roundworm Baylisascaris procyonis, the larval stage of which can cause disease in >150 species of birds and mammals including humans. This thesis investigated the ecology and epidemiology of B. procyonis in Ontario. Knowing that the larval stage of the parasite can cause neurological disease in a wide variety of host species, I performed a retrospective analysis of causes of morbidity and mortality in Ontario rodents and lagomorphs to determine the impact of this parasite in the province. The most common diagnosis across all species was encephalitis consistent with neural larval migrans, and the odds of this diagnosis were significantly greater for groundhogs (Marmota monax) than other species investigated. After establishing the parasite as a common cause of mortality, I performed a literature review to identify knowledge gaps and inconsistencies regarding host and environmental risk factors associated with B. procyonis in raccoons. Using a data set of 1539 raccoons submitted to the Canadian Wildlife Health Cooperative between 2013 and 2016, I investigated the influence of host factors, human population size, and predominate human land use type on B. procyonis infection in raccoons, finding previously reported associations and several interactions between variables. I then used spatial, temporal, and spatio-temporal scan statistics to identify regions and time periods with high or low clusters of infection prevalence, identifying a spatial and space-time cluster that included a portion of the greater Toronto area. With this knowledge, I performed an additional risk factor analysis using raccoons submitted to the Canadian Wildlife Health Cooperative from Toronto examining specific environmental factors and their association with infection prevalence. Many identified relationships were non-linear or involved interactions with host factors, emphasizing the complexity of host-pathogen-environment relationships. This thesis adds to the current understanding of the ecology of B. procyonis, particularly with respect to the influence of environmental factors on infection. It also demonstrates an approach to investigating environmental factors at multiple scales which can be applied to other host pathogen systems.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| 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".