Musculotendon excursion potential, tendon slack and muscle fibre length: the interaction of the canine gastrocnemius muscle and tendon
Bibliographic record
Abstract
Although the form-function relation of muscles and tendons has been studied extensively, little in vivo data exist on the musculotendon properties of the gastrocnemius complex in dogs. Using a combination of ultrasound and 3D motion tracking, musculotendon parameters were obtained in vivo from the lateral gastrocnemius muscle and the gastrocnemius tendon in nine healthy Labrador Retrievers. These parameters include musculotendon length and excursion potential, tendon slack length, muscle belly length, muscle fibre length, pennation angle and architectural index. This study also examined the variation of muscle and tendon length contributions to musculotendon length, as well as the relation between musculotendon excursion potential and muscle fibre length or tendon length. To facilitate comparison between dog breeds, the femur length as a potential scaling parameter was examined. In the Labrador gastrocnemius musculotendon complex, the tendon contributes 41% (± 9%) of musculotendon length. In longer musculotendon complexes, the contribution of the muscle belly increases while the tendon contribution decreases. Longer muscle belly and musculotendon complexes were, however, associated with shorter muscle fibres. No significant relations were found between musculotendon excursion potential and muscle fibre length or tendon slack length, and femur length did not prove to be a reliable scale factor for the length-related musculotendon parameters examined in this study. Longer musculotendon complexes exhibit relatively longer muscle bellies, which are in turn associated with shorter muscle fibre lengths. This trade-off between gastrocnemius muscle belly length and muscle fibre length might have the advantage that muscle volume stays constant regardless of the length of the limbs.
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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 | 0.001 |
| 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".