Radiographic Assessment of Normal Coxofemoral Joints of Labrador Retrievers
Bibliographic record
Abstract
Objectives: To quantify lateral and dorsal acetabular femoral head (AFH) coverage in normal coxofemoral joint of Labrador retrievers and to evaluate the degree of steepness of the cranial acetabular edge (acetabular slope ‘AS’ angle) and inclination angle (IA) in normal hips. Methods: The investigated group was categorized as normal coxofemoral joints according to the morphometric criteria established by the FCI system. Centre-edge (CE) angle, Norberg angle (NA), indices of dorsal AFH coverage width and area, acetabular index angle, and inclination angle were determined. Mean (±SD) values related to all parameters were calculated. A spearman correlation coefficient determined the relationship between selected variables . Results: Significant correlations were identified between NA and CE-angle (rs= 0.58, P< 0.0001), and between the width and area of dorsal AFH coverage (rs= 0.86, P< 0.0001). Weak correlations were determined between the radiographic techniques used to assess lateral versus dorsal AFH coverage. A weak negative correlation (rs = -0.48, P < 0.0001) was determined between acetabular slope (AS) angle and CE angle. Inclination angle did not correlate with any of other radiographic measurements reported in our study. Conclusions: The present study concluded that, radiographic evaluation of dorsal AFH coverage width and area index, CE-angle and IA (Inclination angle) during selective breeding reduce the prevalence of CHD among offspring. Coxofemoral joints with dorsal AFH coverage width index ≥ 55%, area index ≥ 59%, CE-angle ≥ 27o and IA ranges between 130o-132o are expected to be perfectly normal.
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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 | 0.003 | 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".