Sequential measurements of the tibial plateau angle in large-breed, growing dogs
Bibliographic record
Abstract
OBJECTIVES: To determine the earliest age that canine tibial plateau angles (TPAs) can be reliably measured and determine whether TPAs change during long bone growth. ANIMALS: 10 Labrador Retrievers and 20 Labrador Retriever-hound crossbreeds. PROCEDURE: Stifle joints were radiographed every 2 months from 8 weeks of age to radiographic closure of the tibial physes. Four examiners radiographically evaluated TPA, physeal closure status (ie, complete or incomplete) of the proximal and distal tibial physis, and whether anatomic TPA measurement landmarks were sufficiently visible (LSV) or insufficiently visible (LIV) for accurate measuring. Linear regression analysis was performed to detect change in TPAs over time. Mean ages with 95% confidence intervals (CIs) were determined for dogs with radiographs classified as LIV and LSV. RESULTS: TPAs did not change from 90 days of age to physeal closure. Mean age for dogs with radiographs classified as LIV was 70.2 days (95% CI, 68.12 to 72.28 days), with no dog with LIV radiographs over 81 days of age. Mean age for dogs with radiographs classified as LSV was 85.5 days (CI, 76.73 to 94.27 days). CONCLUSIONS AND CLINICAL RELEVANCE: TPAs in Labrador Retrievers and Labrador Retriever-hound crossbreeds can be measured accurately after 90 days of age, and earlier attempts to measure result in falsely low TPA measurements. Measuring TPAs in growing dogs may allow earlier detection of premature physeal closures. As more is learned about the role of theTPA in cranial cruciate ligament injury, early treatment may be possible for growing dogs with cruciate ligament injuries and excessive tibial slope.
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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 | 0.000 |
| 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".