Contribution of Habitual Activity to Cruciate Ligament Rupture in Labrador Retrievers
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to describe the contribution of signalment and habitual activity in the development of cruciate ligament rupture (CR) in Labrador Retrievers. STUDY DESIGN: Four hundred and twelve client-owned purebred Labrador Retrievers were recruited. Dogs were assigned either as affected with CR or as controls based on signalment, physical examination and radiographic evidence of disease. Clients were asked to complete a questionnaire related to signalment, concurrent disease and a questionnaire pertaining to their dog's activity before development of CR or general activity during the dog's most active years. RESULTS: Habitual activity was not significantly different between dogs affected with CR and controls. There was no significant difference in neuter status or body weight between CR affected dogs and controls. Labrador Retrievers with a yellow coat, and Labradors that did not maintain an optimal body weight in the opinion of their veterinarian were at increased risk of developing CR. CONCLUSIONS: Habitual activity level is not a risk factor for development of CR in Labrador Retrievers. Our study did not show neuter status, sex or body weight to be risk factors for CR. However, coat colour and not sustaining optimal body condition are significant risk factors for CR.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".