Survey investigating the reasons why UK‐based gundogs ceased working between 2010 and 2019
Bibliographic record
Abstract
BACKGROUND: To determine the longevity of the working life of gundogs in the UK, whether owners' considered retirement was premature and to identify risk factors associated with such work. METHODS: A web-based survey seeking owner information as to the longevity of their dogs' working life and why they were retired, euthanised or died. The sample population is six hundred sixty-five dogs. RESULTS: The median age at which Springer spaniels stopped work was 11 years and for Cocker spaniels, it was 9 years. The median age for Labrador retrievers was 10 years; for Golden retrievers, 11 years and Flat-coated retrievers, 9.5 years. Cocker spaniels stopped work at a significantly younger age than Springer spaniels (p = 0.0003) or Labrador retrievers (p = 0.0407). There was no significant difference between the other major breeds. The majority of owners (54.3%) were satisfied with the working lifespan of their dog. Seventy per cent of dogs were retired, the three most prevalent reasons being lameness (25.2%), old age (23.7%) and deafness (7.8%). Forty-four dogs died (6.6%) and 158 (24%) were euthanised, with cancer (58%) being the most common reason. CONCLUSIONS: No work-related issues were identified and gundogs appear to have similar causes of mortality to the general canine population.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".