Evaluation of the prevalence of <i>Echinococcus multilocularis</i> in dogs that visit off‐leash dog parks in southern Ontario, Canada
Bibliographic record
Abstract
Prior to 2012, Echinococcus multilocularis was not known to occur in any host in Ontario, Canada. However, since that year, five cases of alveolar echinococcosis have been diagnosed in dogs that resided at the western end of Lake Ontario. In addition, E. multilocularis has been shown to be a common infection in wild canids (i.e. coyotes and foxes) across southern Ontario with a high-risk infection cluster in the area surrounding the western shores of Lake Ontario and northern shores of Lake Erie. In regions endemic for E. multilocularis, dog ownership is considered a risk factor for human alveolar echinococcosis. A study was therefore carried out to determine the prevalence of E. multilocularis intestinal infections in dogs within the high-risk infection cluster. From May to November 2018, faecal samples were collected from 477 dogs aged ≥6 months that visited 12 off-leash dog parks in the Halton, Hamilton and Niagara public health units. Faecal samples were analysed via a magnetic capture probe DNA extraction and real-time PCR method for E. multilocularis DNA. Overall, 0% (97.5% CI: 0%-0.80%) of samples tested positive. This result informs preventive recommendations for E. multilocularis infections in dogs in this region.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".