Body composition of medium to giant breed dogs with or without cranial cruciate ligament disease
Bibliographic record
Abstract
OBJECTIVE: To describe the body composition of dogs with or without cranial cruciate ligament (CCL) disease. STUDY DESIGN: Cross-sectional. ANIMALS: Adult dogs in which CCL disease was diagnosed (n = 30) and adult dogs without clinical signs of orthopedic disease (n = 30). METHODS: Body weight, body condition score, and muscle condition score (MCS) were recorded. Body composition of the whole body and pelvic limbs were assessed by dual-energy x-ray absorptiometry. Body condition score, whole body, and pelvic limb body composition measurements were compared by using general linear mixed-model analysis of variance. Muscle condition score between groups was assessed by using a Mann-Whitney U test, while paired data were analyzed by using a Wilcoxon signed-rank test. RESULTS: Body fat percentage (P < .0001) was higher in affected dogs (38.78% ± 1.40) than in control dogs (27.49% ± 1.24). Affected dogs had lower MCS (1.90 ± 0.13, P < .0001) compared with control dogs (2.77 ± 0.08). The affected pelvic limb of affected dogs contained less lean soft tissues (P < .0001) but more fat (P = .0451) compared with the contralateral pelvic limb. CONCLUSION: Dogs with CCL disease were overweight compared with the control group. CLINICAL SIGNIFICANCE: Dogs that are overweight may be predisposed to developing CCL disease. Body composition changes in the pelvic limbs should be considered when managing the care of these dogs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".