Assessment of bone mineral density of the femoral head in dogs with early osteoarthritis
Bibliographic record
Abstract
OBJECTIVE: To compare the bone mineral density (BMD) of the proximal portion of the femur in dogs with and without early osteoarthritis secondary to hip dysplasia. ANIMALS: 24 dogs (3 Greyhounds, 6 Labrador-Greyhound crossbreeds, and 15 Labrador Retrievers). PROCEDURE: Computed tomography (CT) of the pelvis, including a bone-density phantom, was performed for each dog. Centrally located transverse CT slices and a computer workstation were used to identify 16 regions of interest (ROIs) in the proximal portion of the femur. For each ROI, the mean Hounsfield unit value was recorded; by use of the bone-density phantom and linear regression analysis, those values were converted to equivalent BMD (eBMD). Mean eBMD values for the subchondral and nonsubchondral ROIs in dogs with and without osteoarthritis (determined at necropsy) were compared. A mixed-model ANOVA and post hoc linear contrasts were used to evaluate the effects of osteoarthritis, breed, and sex on the BMD value. RESULTS: At necropsy, osteoarthritis was detected in 14 hip joints in 9 dogs; all lesions included early cartilage fibrillation. After adjusting for breed and sex, eBMD in subchondral ROIs 8 and 12 (adjacent to the fovea) were 8% and 6% higher, respectively, in osteoarthritis-affected dogs, compared with unaffected dogs; in the nonsubchondral ROIs, eBMD was 10% higher in osteoarthritis-affected dogs. CONCLUSIONS AND CLINICAL RELEVANCE: Compared with findings in unaffected dogs, increased eBMD in hip joints of dogs with early osteoarthritis supports a strong relationship between the subchondral and epiphyseal regions and articular cartilage in the pathogenesis and progression of osteoarthritis.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".