Twitch mechanical properties after repeated eccentric exercise of the elbow flexors
Bibliographic record
Abstract
The purpose of this study was to assess if the protective adaptation after eccentric exercise affects changes of twitch contractile properties of the biceps brachii muscle. Maximal isometric torque (MVC), twitch contractile properties, muscle soreness, and relaxed elbow angle (RANG) assessments were measured in 12 untrained, right-handed male volunteers (age, 23 ± 2 years; height, 182 ± 5 cm; mass, 75 ± 7 kg) before, immediately after, 48 h, and 120 h following each bout of eccentric exercise that consisted of 30 repetitions of lowering a dumbbell adjusted to 75% of each individual's maximal isometric torque of the right elbow flexors. MVC, peak twitch torque, maximal rate of twitch torque development, maximal rate of relaxation, muscle soreness, and RANG changes were significantly attenuated after the second bout of eccentric exercise when compared with the first bout. In contrast, time to twitch peak torque and half relaxation time did not change significantly after both the first and the second bout. The findings indicate that the mechanisms responsible for rapid adaptation affect some twitch mechanical properties such as peak torque, maximal rate of torque development, and maximal rate of relaxation but not time to peak torque and half relaxation time.
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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".