Validation of goniometric measurements of rotational laxity of the canine stifle
Bibliographic record
Abstract
Objective: To validate goniometric measurements of stifle rotational laxity in dogs in an ex vivo study and determine their reproducibility in a clinical setting. Methods: In phase 1, 16 normal pelvic limbs were harvested from 8 canine cadavers. Goniometric measurements, including tibial torsion (TT) and internal and external rotation of the stifle were compared within limbs and between groups before and after each of the following modifications: transection of the cranial cruciate ligament (CCL) as a model of rotational hyperlaxity (CCL deficiency [CCLD]), rotational osteotomy as a model of TT, and CCLD+TT. A lateral fabella suture (LFS) was then placed in each limb before measurements were repeated. Phase 2 was a clinical prospective study of 51 awake dogs (102 limbs). Torsion and stifle rotations were measured by 2 investigators, 1 in triplicate. Correlation coefficients were calculated to assess intra- and interinvestigator reproducibility. Results: In phase 1, internal rotation increased by 10.6 ± 7.2° after CCL transection. Placement of an LFS did not influence TT but decreased internal rotation within limbs. Internal rotation of the stifle was increased in all CCLD limbs (CCLD, 32.6 ± 7.6°; CCLD+TT, 33.0 ± 12.3°) compared to intact limbs (24.4 ± 5.8°) and CCLD limbs repaired with LFS (6.3 ± 5.1°). In phase 2, correlation coefficients within and between investigators were > 0.9 for TT and internal rotation angles of the stifle. Conclusions: Goniometry allowed the detection of experimentally induced hyperlaxity and was reproducible in awake dogs. Clinical Relevance: Goniometric assessment of stifle rotation should be considered during routine orthopedic examination.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".