Analysis of risk factors for elbow dysplasia in giant breed dogs
Bibliographic record
Abstract
OBJECTIVE: Identify radiographic risk factors for development of elbow dysplasia in giant breed dogs less than one year of age. METHODS: Twenty-five giant breed puppies (Bernese Mountain dogs, English Mastiff, and Newfoundland) were studied. Both elbows of each dog were radiographed monthly from two to six months of age, then every other month until radial and ulnar physeal closure, followed two months later by bilateral elbow computed tomography. Radiographic parameters measured included the presence or absence of a separate centre of ossification of the anconeal process (SCOAP), medial coronoid disease (MCD), ununited anconeal process, humeral osteochondrosis, elbow incongruity, as well as the length of the radius and ulna, radius-to-ulna ratio, and date of closure of the radial and ulnar physes. RESULTS: Fifteen dogs completed the study. Two Bernese Mountain dogs were diagnosed with MCD. Risk factors significantly associated with medial coronoid disease included dyssynchronous physeal closure and a decreased radius-to-ulna ratio, both detected between eight to 11 months of age. A separate centre of ossification of the anconeal process was present in 60% of the dogs, and was not a risk factor for development of elbow dysplasia. CLINICAL SIGNIFICANCE: Transient, dyssynchronous growth of the radius and ulna may be a risk factor for development of MCD in Bernese Mountain dogs. Dyssynchronous physeal closure or decreased radius-to-ulna ratio prior to radiographic closure of the distal ulnar and radial physes warrants further study in Bernese Mountain dogs and other breeds subject to MCD development.
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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) | 0.001 | 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".