PREDISPOSITION OF DOG BREEDS TO RUPTURE OF THE CRANIAL CRUCIATE LIGAMENT
Bibliographic record
Abstract
Obtaining more data on breed predisposition of dogs to the cranial cruciate ligament (CCL) rupture and data on accompanying abnormalities of joints of pelvic limbs affected by the CCL rupture may help in answering some questions concerning the etiology and pathogenesis of the disorder. In 183 patients affected by the CCL rupture out of the total of 11579 dogs, evaluated and/or treated in the Clinic of Surgery and Orthopedics at the Veterinary and Pharmaceutical University Brno from January 1997 till April 2000, the breed, weight, sex and concurrent joint abnormalities of pelvic limbs (hip dysplasia, patellar luxation and osteochondrosis of the stifle joint) were recorded. A total of 213 stifle joints (16.39 % of cases were bilateral CCL ruptures) were affected. Increased breed predisposition (χ2-test; p < 0.01) was found in American Staffordshire Terrier, Rottweiler, Brazilian Fila, Labrador Retriever, American Cocker Spaniel, Chow Chow, German Shorthaired Pointer, Saint Bernard and Bullmastiff and also on the 5 % level of significance in Boxer. Contrary to published data, the high incidence of CCL rupture was found in Brazilian Fila (13.43 % of prevalence). The risk of the CCL rupture in German Shepherd Dog was significantly
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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) | 0.003 | 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".