Breed susceptibility for common surgically treated orthopaedic diseases in 12 dog breeds
Bibliographic record
Abstract
BACKGROUND: A retrospective case-control study was conducted to estimate breed predisposition for common orthopaedic conditions in 12 popular dog breeds in Norway and Sweden. Orthopaedic conditions investigated were elbow dysplasia (ED); cranial cruciate ligament disease (CCLD); medial patellar luxation (MPL); and fractures of the radius and ulna. Dogs surgically treated for the conditions above at the Swedish and Norwegian University Animal Hospitals between the years 2011 and 2015 were compared with a geographically adjusted control group calculated from the national ID-registries. Logistic regression analyses (stratified for clinic and combined) were used to calculate odds ratios (OR) and 95% confidence intervals. Mixed breed dogs were used as reference. RESULTS: Breeds found at-risk for ED were the Labrador retriever (OR = 5.73), the Rottweiler (OR = 5.63), the German shepherd dog (OR = 3.31) and the Staffordshire bull terrier (OR = 3.08). The Chihuahua was the only breed where an increased risk for MPL (OR = 2.80) was identified. While the Rottweiler was the only breed predisposed for CCLD (OR = 3.96), the results were conflicting for the Labrador retriever (OR = 0.44 in Sweden, 2.85 in Norway); the overall risk was identical to mixed-breed dogs. CONCLUSIONS: Most results are in concordance with earlier studies. However, an increased risk of CCLD was not identified for the Labrador retriever, the Staffordshire bull terrier was found to have an increased risk of ED and some country-specific differences were noted. These results highlight the importance of utilising large caseloads and appropriate control groups when breed susceptibility is reported.
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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 | 0.001 | 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".