Both the elongation of attached crossbridges and residual force enhancement contribute to joint torque enhancement by the stretch-shortening cycle
Bibliographic record
Abstract
This study examined the influence of the elongation of attached crossbridges and residual force enhancement on joint torque enhancement by the stretch-shortening cycle (SSC). Electrically evoked submaximal tetanic plantar flexions were adopted. Concentric contractions were evoked in the following three conditions: after 2 s isometric preactivation (ISO condition), after 1 s isometric then 1 s eccentric preactivation (ECC condition), and after 1 s eccentric then 1 s isometric preactivation (TRAN condition). Joint torque and fascicle length were measured during the concentric contraction phase. While no differences in fascicle length were observed among conditions at any time points, joint torque was significantly higher in the ECC than TRAN condition at the onset of concentric contraction. This difference would be caused by the dissipation of the elastic energy stored in the attached crossbridges induced by eccentric preactivation in TRAN condition due to 1 s transition phase. Furthermore, joint torques observed 0.3 and 0.6 s after concentric contraction were significantly larger in the ECC and TRAN conditions than in the ISO condition while no difference was observed between the ECC and TRAN conditions. Since the elastic energy stored in the attached crossbridges would have dissipated over this time frame, this result suggests that residual force enhancement induced by eccentric preactivation also contributes to joint torque enhancement by the SSC.
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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) | 0.002 | 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".