Shape and Variability of the Normal Medial Coronoid Process by Computed Tomography in Young Adult Labrador Retrievers
Bibliographic record
Abstract
Medial coronoid process disease (MCPD) is the most frequently observed cause of elbow dysplasia, resulting in lameness in young, fast-growing large-breed dogs, including Labrador Retrievers (LRs). Computed tomography (CT) is the diagnostic imaging modality of choice for evaluating the medial coronoid process (MCP), as it is noninvasive and eliminates superimposition of the process by the radial head. This retrospective descriptive study aimed to describe the shape of the normal MCP on CT, to assess its variability within the LR breed, and to determine the normal Hounsfield units (HUs) of the MCP, medial radial head (MRH), and lateral radial head (LRH). Normal elbow CT studies of 51 South African guide dog LRs were reviewed. Using a repeatable imaging alignment technique, three principal MCP shapes were identified: ovoid, triangular, and softly pointed and were found to be dependent on the level of assessment. Males had significantly lower mean MCP HU compared to females. The mean HU of the MRH was consistently higher than the LRH and was also greater in attenuation on subjective assessment. Measuring MCP and radial head HU too proximally was suboptimal, as volume averaging was frequently encountered. The results of this study showed that although different alignment techniques may result in HU variations, they will not affect the HU to such an extent that the MCP would be misclassified as abnormal.
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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 | 0.003 |
| 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 | 0.001 | 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".