Epidemiological investigation of euthanasia in an Ontario animal shelter
Bibliographic record
Abstract
Objectives The objective was to evaluate factors associated with euthanasia in an animal shelter in Kitchener-Waterloo, Ontario, Canada. Methods Data from 3737 cats admitted to the shelter between January and December 2011 were evaluated. Results Overall, 1989/3737 (53%) of admitted cats were euthanized. Male cats had greater odds of being euthanized than females (odds ratio [OR] 1.63, 95% confidence interval [CI] 1.29-2.05; P <0.001) and surrendered cats were more likely to be euthanized than strays (OR 38.0, 95% CI 14.8-97.69; P <0.001). Black cats were more likely to be euthanized than cats of another color (OR 1.45, 95% CI 1.16-1.80; P <0.001). Cats that spent >5 days in the shelter were more likely to be euthanized than those that spent <5 days in the shelter (OR 1.57, 95% CI 1.25-1.97; P <0.001). Cats that spent >20 days in the shelter were less likely to be euthanized than those that spent <5 days in the shelter (OR 0.26, 95% CI 0.19-0.34; P <0.001). Age, an age quadratic term, neuter status and interactions among these variables were statistically significant; the odds of unneutered animals being euthanized was high and relatively stable across age groups, but in neutered animals the odds of being euthanized increased with age before plateauing in older cats. Conclusions and relevance With >50% of the cats admitted to the shelter in 2011 euthanized, it is important to understand the contributing risk factors that predispose shelter cats to euthanasia and what changes can be made to the shelter system and in owner education to lower the incidence of euthanasia.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".