Muscle Coordination and Locomotion in Humans
Bibliographic record
Abstract
Locomotion is a semi-automatic daily task. Several studies show that muscle activity is fairly stereotyped during normal walking. Nevertheless, each human leg contains over 50 muscles and locomotion requires flexibility in order to adapt to different conditions as, for instance, different speeds, gaits, turning, obstacle avoidance, altered gravity levels, etc. Therefore, locomotor control has to deal with a certain level of flexibility and non-linearity. In this review, we describe and discuss different findings dealing with both simplicity and variability of the muscular control, as well as with its maturation during development. Despite complexity and redundancy, muscle activity patterns and spatiotemporal maps of spinal motoneuron output during human locomotion show both stereotypical features as well as functional re-organization. Flexibility and different solutions to adjust motor patterns should be considered when considering new rehabilitation strategies to treat disorders involving deficits in gait.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".