Effect of adding single-joint exercises to a multi-joint exercise resistance-training program on strength and hypertrophy in untrained subjects
Bibliographic record
Abstract
The aim of this study was to examine the effect of adding single-joint (SJ) exercises to a multi-joint (MJ) exercise resistance-training program on upper body muscle size and strength. Twenty-nine untrained young men participated in a 10-week training session. They were randomly divided in 2 groups: the MJ group performed only MJ exercises (lat pulldown and bench press); the MJ+SJ group performed the same MJ exercises plus SJ exercises (lat pulldown, bench press, elbow flexion, and elbow extension). Before and after the training period, the muscle thickness (MT) of the elbow flexors was measured with ultrasound, and peak torque (PT) was measured with an isokinetic dynamometer. There was a significant (p < 0.05) increase in MT (6.5% for MJ and 7.04% for MJ+SJ) and PT (10.40% for MJ and 12.85% for MJ+SJ) in both groups, but there were no between-group differences. Therefore, this study showed that the inclusion of SJ exercises in a MJ exercise training program resulted in no additional benefits in terms of muscle size or strength gains in untrained young men.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 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".