Evaluation of a radiographic caudolateral curvilinear osteophyte on the femoral neck and its relationship to degenerative joint disease and distraction index in dogs
Bibliographic record
Abstract
OBJECTIVE: To determine prevalence of a radiographic caudolateral curvilinear osteophyte (CCO) on the femoral neck in various breeds and age groups of dogs and to evaluate its contemporaneous relationship with degenerative joint disease (DJD) and distraction index (DI). DESIGN: Cross-sectional prevalence study. ANIMALS: 25,968 dogs, including 3,729 German Shepherd Dogs, 4,545 Golden Retrievers, 6,277 Labrador Retrievers, and 1,191 Rottweilers. PROCEDURE: Data from the University of Pennsylvania Hip Improvement Program database were analyzed, including ventrodorsal hip-extended, compression, and distraction radiographs. The CCO and radiographic signs of DJD were considered independent events and were interpreted as either present or absent. Statistical methods were used to evaluate the CCO as a possible risk factor for DJD and assess its association with DI, as measured by use of distraction radiography. RESULTS: When all breeds were pooled, DJD was detected in 8.6% of dogs, and the CCO was detected in 21.6% of dogs. Among dogs with a CCO, 25.1% had radiographic evidence of DJD. Among dogs without a CCO, only 4% had DJD. Dogs with a CCO were 7.9 times as likely to have DJD as were those without a CCO. Additionally, DI, weight, and age were significant risk factors for the CCO. CONCLUSION AND CLINICAL RELEVANCE: Results confirm the contemporaneous association between the CCO and DJD and that passive hip laxity, as measured by use of the DI, is associated with both the CCO and DJD.
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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 | 0.001 | 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".