Light concentric exercise has a temporarily analgesic effect on delayed-onset muscle soreness, but no effect on recovery from eccentric exercise
Bibliographic record
Abstract
This study investigated the hypothesis that a bout of light concentric exercise (LCE) would alleviate delayed-onset muscle soreness (DOMS) and enhance recovery from muscle damage. Fourteen subjects performed two bouts of 60 maximal eccentric actions of the elbow flexors (Max-ECC) separated by 2-4 weeks. One arm performed LCE (600 elbow flexion and extension actions with minimal force generation) 1, 2, 3, and 4 d after Max-ECC; the contralateral (control) arm performed only Max-ECC. Changes in maximal isometric and isokinetic strength, range of motion (ROM), upper arm circumference, and muscle soreness and tenderness were assessed before and immediately after LCE bouts. Changes in these measures and plasma creatine kinase (CK) activity for 7 d after Max-ECC were compared between the control and LCE arms using 2-way repeated measures analysis of variance (ANOVA). Significant (p < 0.05) decreases in muscle soreness (approximately 40%) and tenderness (approximately 40%) were evident immediately after LCE, which also resulted in small but significant decreases in strength (approximately 15%) and increases in ROM (approximately 5 degrees ). No significant differences in the changes in the measures following Max-ECC were observed between the arms. These results suggest that LCE has a temporary analgesic effect on DOMS, but no effect on recovery from muscle damage.
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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 | 0.000 |
| 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".