Bibliographic record
Abstract
The analysis of elbow radiographs of 21 272 dogs, examined during 1988-2005, enabled us to estimate the frequency of canine elbow dysplasia in 90 breeds of dogs. Relation between breeds and incidence of elbow dysplasia was established statistically. The percentage of affected specimens was surprisingly low at 0.7% (150 dogs), and distinctly lower than the percentages reported by several authors in Germany, the USA, and other countries. The highest number of dogs affected was found in 47 (1.7% of total number studied) German Shepherds, in 25 Rottweilers (2%), and in 17 Dachshunds (0.5%). Breeds most often affected were of FCI group II, namely English Mastiffs (9%), Dogue de Bordeaux (8.5%), Neapolitan Mastiffs (8.3%), and Newfoundlands (4.6%). Elbow dysplasia was also found with significant frequency in breeds of the FCI group VIII – Labrador Retrievers (4.3%) and Golden Retrievers (4.4%). Fragmented coronoid process (FCP) was most frequently diagnosed (58.0% out of 150 affected specimens). Ununited anconeal process (UAP), was diagnosed in 32.0%. FCP and UAP together were present in 6.7% of the dysplastic specimens. No cases of osteochondritis dessecans and joint incongruity were found. UAP cases were most common in German Shepherds, while FCP occurred most frequently in Dogues de Bordeaux and Rottweilers.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| 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".