Radiographic and computed tomographic assessment of the development of the antebrachia and elbow joints in Labrador Retrievers with and without medial coronoid disease
Bibliographic record
Abstract
OBJECTIVES: To compare the development, monitored by radiography and computed tomography, of the antebrachia and elbow joints in seven Labrador Retrievers with healthy elbow joints and in seven Labrador Retrievers that developed medial coronoid disease (MCD), in order to determine whether disturbances in the development of the antebrachia and elbow joints, between the age of six and 17 weeks may lead to medial coronoid disease. METHODS: A prospective study of 14 Labrador Retrievers in their active growth stage was performed. The development of the antebrachia and elbow joints was assessed between six and 17 weeks of age using radiography and computed tomography determining the development of secondary ossification centres, radioulnar length ratio, radial angulation, and inter-relationship between the humerus, ulna and radius. RESULTS: For the parameters of ossification of secondary ossification centres, radioulnar length ratio, radial angulation, and joint congruence evaluation, there was no significant difference in the development of the antebrachia and elbow joints of seven Labrador Retrievers positive and seven Labrador Retrievers negative for MCD at the age of six to 17 weeks. CLINICAL SIGNIFICANCE: These findings demonstrate that the development of MCD in the Labrador Retrievers in our study was not related to any disturbance in the development of the antebrachia and elbow joints during the rapid growth phase.
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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 | 0.000 |
| 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".