Kinetic and kinematic analysis of the right hind limb during trotting on a treadmill in Labrador Retrievers presumed predisposed or not predisposed to cranial cruciate ligament disease
Bibliographic record
Abstract
OBJECTIVE: To identify gait characteristics during trotting on a treadmill in nonlame Labrador Retrievers presumed predisposed or not predisposed to cranial cruciate ligament disease (CCLD). ANIMALS: Clinically normal Labrador Retrievers presumed predisposed (n = 10) or not predisposed (7) to CCLD. PROCEDURES: The right hind limb of each dog was classified by use of a predictive score equation that combined tibial plateau angle and femoral anteversion angle as presumed predisposed (high score [> -1.5]) or not predisposed (low score [≤ -1.5]) to CCLD. Tarsal joint, stifle joint, and hip joint kinematics, net moments, and powers were computed. RESULTS: The stifle joint was held at a greater degree of flexion in limbs presumed predisposed to CCLD (130.9° vs 139.3°). More power was generated by muscles acting on the stifle joint in the early stance phase of limbs presumed to be predisposed to CCLD (2.93 vs 1.64 W/kg). The tarsal joint did not reach the same degree of extension in limbs presumed predisposed to CCLD, compared with that in limbs presumed not predisposed to CCLD (179.0° vs 161.0°). Velocity, stance time, vertical and craniocaudal forces, angular velocities, and net joint muscle moments did not differ between groups. CONCLUSIONS AND CLINICAL RELEVANCE: Gait mechanics of dogs with high (> -1.5) and low (≤ -1.5) tibial plateau angle and femoral anteversion angle scores were characterized on a treadmill, which may help in the identification of dogs predisposed to CCLD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".