Comparison of three distraction methods and conventional radiography for early diagnosis of canine hip dysplasia
Bibliographic record
Abstract
Two radiographic distraction techniques (one employing a wooden lath and, the other, a PennHip distractor), an ultrasonographic distraction method and conventional radiographic Fédération Cynologique Internationale (FCI) hip score were evaluated in eight-month-old Labrador retrievers to determine the most reliable method for predicting radiographic FCI hip score at the age of one year. With reference to the FCI hip score, sensitivity and specificity of the PennHip method were 100 per cent and 54 per cent; sensitivity and specificity of the lath technique were 85 per cent and 71 per cent; whereas they were 62 per cent and 67 per cent for the ultrasonographic method. For all distraction methods, the positive predictive value (PPV) was moderate and the negative predictive value (NPV) was high. Sensitivity, specificity, PPV and NPV were 100 per cent for the FCI hip score. It is concluded that, at the age of eight months, FCI hip score is the most reliable method for predicting FCI hip score at the age of one year in the colony of dogs investigated. Both the PennHip and lath method were also clinically reliable techniques in predicting true negatives. The ultrasonographic distraction method was moderately reliable.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".