Topographic Bone Density of the Radius and Ulna in Greyhounds and Labrador Retrievers With and Without Medial Coronoid Process Disease
Bibliographic record
Abstract
OBJECTIVE: To quantify, using computed tomography (CT), cross-sectional ulnar bone density (UBD), and regional radial bone density (RRBD) at the level of the medial coronoid process (MCP) in elbows with and without medial coronoid process disease (MCPD) and with and without fragmentation of MCP (FCP). STUDY DESIGN: Retrospective clinical case-control and ex vivo study. SAMPLE POPULATION: Labrador Retriever elbows (n = 54) and normal cadaveric Greyhound elbows (11) undergoing elbow CT. MATERIALS AND METHODS: Labrador Retriever elbows were divided into 2 groups: (1) clinically unaffected and (2) MCPD-affected elbows. This 2nd group was subdivided based on the presence of a displaced FCP. UBD was measured linearly, in Hounsfield units (HU) across the widest part of the ulna incorporating the MCP. The radial head was divided into 6 zones, with mean RRBD (HU) calculated for each group. RESULTS: MCPD-affected Labrador Retriever elbows had significantly lower UBD within the MCP with a higher UBD in the cranial ulnar medulla. Lower RRBD was also seen in the radial head adjacent to the MCP in MCPD-affected Labrador Retriever elbows with FCP compared with Labrador Retriever elbows without FCP. Greyhounds had consistently lower RRBD and UBD at the apex of the MCP compared with clinically unaffected Labrador Retriever elbows. CONCLUSIONS: Our results suggest a caudolateral load-transfer shift through the ulna in MCPD-affected elbow joints, unloading the MCP. Changes in regional radial head bone density suggest that the radial head is involved in the pathogenesis of MCPD.
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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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".