The activation time-course of contractile elements estimated from in vivo fascicle behaviours during twitch contractions
Bibliographic record
Abstract
To better understand the cascade from neural activation up to force production within in vivo contracting muscle-tendon units, we estimated activation of contractile elements from experimentally measured human fascicle length change and force using a Hill-type muscle model. The experiment was conducted with respect to twitch contractions of the tibialis anterior muscle at three joint angles. As muscle contractile element force is a function of its length and velocity, the activation of contractile elements was calculated using a Hill-type muscle model and measured data. The results were able to reproduce the continuous rising activation of contractile elements after termination of electromyographic activity, the earlier shift of peak activation in time compared to twitch force, and the differences in time-course activation at three different joint angles. These findings are consistent with the predicted change in the activation of contractile elements from previous reports. Also, the results suggest that the time-course of the activation of contractile elements was greatly influenced by the change in force generating capacities related to both length and velocity, even in fixed end contractions, which could result from muscle-tendon interaction.
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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 | 0.000 | 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) | 0.001 | 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".