Phenotypic hip and elbow dysplasia trends in Rottweilers and Labrador retrievers in South Africa (2007–2015): Are we making progress?
Bibliographic record
Abstract
Canine hip and elbow dysplasia are major orthopaedic problems prevalent the world over, and South Africa is no exception. Hip and elbow dysplasia phenotypic status is certified by a number of different radiographic schemes in the world. South Africa uses the Fédération Cynologique Internationale system to certify hips, and the International Elbow Working Group scheme to certify elbows. One way of reducing these often crippling conditions is by selective breeding using only dogs with no or marginal dysplastic joints. In South Africa, only seven breeds, including the Rottweiler, have breeding restrictions for hip dysplasia. There are no such restrictions for elbow dysplasia. This study assessed the prevalence of hip and elbow dysplasia over a 9-year-period in the Rottweiler and the Labrador retriever in South Africa as evaluated by official national scrutineers. Records from 1148 Rottweilers and 909 Labrador retrievers were obtained and were graded as normal or dysplastic, and numerical values were also evaluated. Data were compared between the two breeds, males and females as well as over time and were compared with similar data of the Orthopaedic Foundation for Animals in the United States. The prevalence values for hip dysplasia in Rottweilers and Labrador retrievers were 22% and 31%, respectively, whereas for elbow dysplasia the values were 39% and 19%, respectively. In Labrador retrievers, this incidence was much higher than in the American population. Rottweiler hip and elbow dysplasia numerical scores significantly improved over time, whereas in Labrador retrievers, only hip dysplasia showed a minor but significant improvement. This study proved that prescribing minimum breeding requirements, as in the Rottweiler in this study, significantly improved the breeding stock, suggesting that minimum hip and elbow breeding requirements should be initiated for all breeds at risk of these often crippling conditions.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".