AGE‐RELATED THORACIC RADIOGRAPHIC CHANGES IN GOLDEN AND LABRADOR RETRIEVER MUSCULAR DYSTROPHY
Bibliographic record
Abstract
Golden retriever and Labrador retriever muscular dystrophy are inherited progressive degenerative myopathies that are used as models of Duchenne muscular dystrophy in man. Thoracic lesions were reported to be the most consistent radiographic finding in golden retriever dogs in a study where radiographs were performed at a single-time point. Muscular dystrophy worsens clinically over time and longitudinal studies in dogs are lacking. Thus our goal was to describe the thoracic abnormalities of golden retriever and Labrador retriever dogs, to determine the timing of first expression and their evolution with time. To this purpose, we retrospectively reviewed 390 monthly radiographic studies of 38 golden retrievers and six Labrador retrievers with muscular dystrophy. The same thoracic lesions were found in both golden and Labrador retrievers. They included, in decreasing frequency, flattened and/or scalloped diaphragmatic shape (43/44), pulmonary hyperinflation (34/44), hiatal hernia (34/44), cranial pectus excavatum (23/44), bronchopneumonia (22/44), and megaesophagus (14/44). The last three lesions were not reported in a previous radiographic study in golden retriever dogs. In all but two dogs the thoracic changes were detected between 4 and 10 months and were persistent or worsened over time. Clinically, muscular dystrophy should be included in the differential diagnosis of dogs with a combination of these thoracic radiographic findings.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".