Muscle coordination is key to the power output and mechanical efficiency of limb movements
Bibliographic record
Abstract
The purpose of this study was to determine which features of muscle mechanics and muscle coordination affect the power output from a limb during locomotion. Eight subjects were tested while cycling at maximum exertion for 25 min on a stationary dynamometer. Cadence and load were varied to span a range of power outputs and myoelectric activity was measured from 10 muscles in the leg. Cycle-by-cycle variations in muscle coordination, cadence and power output were observed and the EMG intensity across all muscles was used as an estimate of the metabolic cost for each cycle. Data for the cycles at greatest power output were separated into three groups: maximum power, 80% power but lower EMG intensity and 80% power and higher EMG intensity. Torque-angular velocity relations were determined for the ankle and knee joints. During cycling at maximum power output the ankle joint was not extending at the velocity necessary for maximum power output; thus, maximum limb power occurs when some of the individual muscles cannot be generating maximum power output. Increases in EMG intensity occurred with no increase in power output from the limb: these corresponded to decreases in the efficiency and changes in coordination. Increases in power were achieved that were not matched by equivalent increases in EMG intensity, but did occur with changes in coordination. It is proposed that the power output from the limb is limited by the coordination pattern of the muscles rather than the maximum power output from any one muscle itself.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".