Measurement of Femoral Angles in Four Dog Breeds
Bibliographic record
Abstract
OBJECTIVE: To develop a standard method of measurement for femoral angles and report values for normal Labrador Retrievers, Golden Retrievers, German Shepherds, and Rottweilers. STUDY DESIGN: Retrospective evaluation of canine pelvis and femoral radiographs. SAMPLE POPULATION: Radiographs of Labrador Retrievers, Golden Retrievers, German Shepherds, and Rottweilers (n=100 for each breed). METHODS: Anatomic lateral distal and proximal femoral angle, mechanical lateral distal and proximal femoral angle, and femoral angle of inclination were measured from radiographs. RESULTS: For the 4 breeds (Labrador Retrievers, Golden Retrievers, German Shepherds, and Rottweilers, respectively) anatomic lateral distal femoral angles were 97 degrees , 97 degrees , 94 degrees , and 98 degrees ; mechanical lateral distal femoral angles were 100 degrees , 100 degrees , 97 degrees , and 100 degrees ; anatomic lateral proximal femoral angles were 103 degrees , 98 degrees , 101 degrees , and 96 degrees ; mechanical lateral proximal femoral angles were 100 degrees , 95 degrees , 97 degrees , and 93 degrees ; and inclination angles were 134 degrees , 134 degrees , 132 degrees , and 137 degrees . Labrador Retrievers, Golden Retrievers, and Rottweilers had significantly higher values for both anatomic and mechanical lateral distal femoral angle than German Shepherds. Anatomic and mechanical lateral proximal angles were greatest for Labrador Retrievers and lowest for Rottweilers. CONCLUSION: Anatomic and mechanical femoral joint angles vary between breeds of dogs. CLINICAL RELEVANCE: Values for femoral joint angles may be clinically useful for angular limb deformity diagnosis, treatment, and assessment.
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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 | 0.002 | 0.005 |
| 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 | 0.000 |
| 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".