Exploring the geographical distribution of cryptosporidiosis in the cattle population of Southern Ontario, Canada, 2011-2014
Bibliographic record
Abstract
Cryptosporidiosis is an infectious disease of relevance to the cattle industry. The southern region of the Canadian province of Ontario is characterised by widespread cattle farming that is a key contributor to the Canadian dairy industry. Given Ontario's key role in the Canadian dairy industry and the potential impact that cryptosporidiosis can have on cattle operations, identifying areas of increased risk for bovine cryptosporidiosis is important. The primary goal of this study was to explore the distribution of bovine cryptosporidiosis, across the geographical areas served by the 29 Public Health Units (PHUs) of Southern Ontario, in the period 2011-2014. Laboratory data on bovine cryptosporidiosis were collected from the Animal Health Laboratory at the University of Guelph, Canada. Using veterinary clinic locations as a proxy for farm location, choropleth and isopleth maps were produced. Highrisk clusters of bovine cryptosporidiosis were identified using the flexible spatial scan test. Assessment of the potential for spatial misclassification bias resulting from a proxy location variable was conducted. The overall raw farm-level prevalence of bovine cryptosporidiosis was 45% [95% confidence interval, CI: 42%-48%]. A cluster was identified in the central-west region of Southern Ontario (relative risk 1.30 [95% CI: 1.07-1.54, P=0.026]) meaning that cattle in the areas served by the Bruce-Grey-Owen Sound, Huron, Wellington-Dufferin Guelph and Waterloo PHUs were at a higher risk for infection. Given that this area is known for having a high-density of dairy cattle, it should be considered as a target for further surveillance.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".