Repeatability of dorsolateral subluxation scores in dogs and correlation with macroscopic appearance of hip osteoarthritis
Bibliographic record
Abstract
OBJECTIVE: To determine whether dorsolateral subluxation (DLS) scores in young dogs could be used to reliably predict which dogs would develop evidence of hip osteoarthritis and whether DLS scores measured at various ages correlated with each other. ANIMALS: 129 Labrador Retrievers, Greyhounds, and Labrador Retriever-Greyhound crossbreds. PROCEDURES: DLS scores were measured on radiographs taken at 4, 8, and 12 months of age and at necropsy (8 to 36 months of age). At necropsy, the hip joints were examined macroscopically and a score assigned for degree of cartilage degeneration. RESULTS: DLS scores at 4 (n = 35, r(s) = -0.62), 8 (n = 106, r(s) = -0.54), and 12 (n = 15, r(s) = -0.87) months of age were significantly correlated with cartilage degeneration scores, and DLS scores at 8 months of age were significantly correlated with scores obtained at the time of necropsy (n = 39, r(s) = 0.87). The DLS scores at 4 months of age were significantly different from scores at 8 months of age, but scores did not differ significantly thereafter. Likelihood ratios for cartilage lesions for low (< 45%), intermediate (> or = 45 but < or = 55%), and high (> 55%) DLS scores at 8 months of age were 8.0, 2.6, and 0.2, respectively. CONCLUSIONS AND CLINICAL RELEVANCE: Results suggest that DLS score at 8 months of age was a reasonable, albeit imperfect, predictor of the condition of the hip joint cartilage at necropsy. Thus, the DLS method might be useful for early identification of dogs with hip dysplasia.
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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 | 0.004 |
| 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".