Evaluation of the Norberg Angle Threshold: A Comparison of Norberg Angle and Distraction Index as Measures of Coxofemoral Degenerative Joint Disease Susceptibility in Seven Breeds of Dogs
Bibliographic record
Abstract
OBJECTIVE: To evaluate the thresholds of 2 radiographic methods used to determine coxofemoral joint laxity in 7 breeds of dogs. ANIMALS: Three hundred and fifty clinically normal dogs. STUDY DESIGN: Retrospective study. METHODS: Hip radiographs from 7 breeds of dogs were randomly selected from a database. None of the dogs had radiographic evidence of degenerative joint disease (DJD). Distraction index (DI) and Norberg angle (NA) were measured on these radiographs and compared with DI and NA thresholds for diagnosing DJD susceptibility derived from the literature and from evaluated Borzois. Dogs with a NA<105 degrees and a DI of < or =0.32 were considered false-positives and dogs with a NA> or =105 degrees and a DI of >0.32 were considered false-negatives. RESULTS: Mean age of all dogs was 22.9 months. Mean NA for all dogs was 99.37 degrees, and mean DI for all dogs was 0.44. Borzoi mean DI of was significantly less than the mean DI of the other 6 breeds. The highest (most hip laxity) Borzoi DI was 0.32, and the lowest (most hip laxity) Borzoi NA was 99 degrees. False-positive and false-negative diagnoses were identified in 6 of the 7 breeds. CONCLUSIONS: Using the NA threshold of 105 degrees (literature established threshold of susceptibility to DJD) resulted in a high percentage of false-negative and false-positive diagnoses. Breeds like the Labrador Retriever and Rottweiler would have large numbers of hip dysplasia susceptible dogs remain in the breeding population based on this NA threshold. False-positive diagnoses were common in breeds like the Australian Shepherd, Borzoi, and German Shepherd effectively eliminating hip dysplasia nonsusceptible dogs from the breeding population. CLINICAL RELEVANCE: The NA was not an accurate predictor of DJD susceptibility in these 7 breeds of dogs when using a NA threshold of 105 degrees.
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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 | 0.002 | 0.007 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".