Net joint moments and joint powers in horses with superficial digital flexor tendinitis
Bibliographic record
Abstract
OBJECTIVE: To determine whether analysis of net joint moments and joint powers is a suitable technique for evaluation of mechanics and energetics of lameness in horses and to measure effects of superficial digital flexor tendinitis. ANIMALS: 6 sound horses. PROCEDURE: Horses were evaluated before (sound evaluation) and after (lame evaluation) induction of superficial digital flexor tendinitis in 1 forelimb by injection of collagenase. Recordings were made with an optoelectronic system and a force plate as horses trotted. Net joint moments and joint powers in the sagittal plane at each joint in the forelimbs during the stance phase were determined. Peak values were determined, and mechanical energy absorbed and generated at each joint was calculated. Comparisons were made between contralateral limbs during sound and lame evaluations. RESULTS: Lame limbs had significant reductions in peak values for net joint moments on the palmar aspect of metacarpophalangeal (fetlock), carpal, and humeroulnar joints. Total energy absorbed was significantly lower at every joint in lame limbs, compared with compensating limbs. CONCLUSIONS AND CLINICAL RELEVANCE: Horses with superficial digital flexor tendinitis had significant differences between lame and compensating limbs for net joint moments and joint powers at all joints, indicating that the gait of horses with superficial digital flexor tendinitis is energetically inefficient. Assessment of net joint moments and joint powers is a useful tool in evaluating equine lameness.
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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 | 0.000 | 0.001 |
| 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".