The energy of muscle contraction. IV. Greater mass of larger muscles decreases contraction efficiency
Bibliographic record
Abstract
While skeletal muscle mass has been shown to decrease mass-specific mechanical work per cycle, it is not yet known how muscle mass alters contraction efficiency. In this study, we examined the effect of muscle mass on mass-specific metabolic cost and efficiency during cyclic contractions in simulated muscles of different sizes. We additionally explored how tendon and its stiffness alters the effects of muscle mass on mass-specific work, mass-specific metabolic cost and efficiency across different muscle sizes. To examine contraction efficiency, we estimated the metabolic cost of the cycles using established cost models. We found that for motor contractions in which the muscle was primarily active during shortening, greater muscle mass resulted in lower contraction efficiency, primarily due to lower mass-specific mechanical work per cycle. The addition of a tendon in series with the mass-enhanced muscle model improved the mass-specific work and efficiency per cycle with greater mass for motor contractions, particularly with a shorter excitation duty cycle, despite higher predicted metabolic cost. The results of this study indicate that muscle mass is an important determinant of whole muscle contraction efficiency.
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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 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".