Isometric torque and shortening velocity following fatigue and recovery of different voluntary tasks in the dorsiflexors
Bibliographic record
Abstract
The present study was designed to compare the relative influence of various fatigue-related factors involved in isometric and dynamic task failure following an equivalent decrease in isometric maximum voluntary contraction (MVC) torque. Using a similar duty cycle (~1-s contraction per 2 s) and contraction load (50% of MVC), 9 young males performed in the dorsiflexors a dynamic task, and on a separate occasion an intermittent isometric task, to an equal decrease in isometric MVC torque. Dynamic contractions had greater motor unit activation and maximum rate of torque development, and required fewer contractions to task failure than the isometric task, indicating a faster development of fatigue during the velocity-dependent dynamic contractions. Peripheral factors, rather than impairments in voluntary drive, were responsible for the equivalent decrease in MVC torque at task failure and its subsequent incomplete recovery. These included, for both tasks, similar changes during fatigue and recovery in voluntary isometric MVC torque, shortening velocity, stimulated twitch and 50 Hz torque, and 50 Hz maximum rate of relaxation. Irrespective of the task, however, the greater reduction in shortening velocity at task failure and its subsequent faster recovery than MVC torque suggest that changes in metabolites affect velocity to a greater extent than isometric torque.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".