Variability of limb muscle size in young men
Bibliographic record
Abstract
The purpose of this study was to determine the interindividual variability of the upper and lower limb muscle size in young men. Subjects were 655 Japanese men aged 18-39 years. They were sedentary and mildly to highly active individuals, including college athletes of various sports. Muscle thicknesses at each of the anterior and posterior portions of the upper arm, thigh, and lower leg were measured using B-mode ultrasonography. Interindividual variability of muscle thickness was evaluated by coefficients of variation (CVs). The CVs of muscle thicknesses were found to be in the order of upper arm posterior (17.7%), thigh anterior (14.8%), thigh posterior (12.6%), upper arm anterior (12.2%), lower leg anterior (9.8%), and lower leg posterior (9.4%). The CVs were significantly different between each pair of measurement sites except for those of upper arm anterior-thigh posterior and lower leg anterior-posterior. These differences remain significant even when the muscle thicknesses were normalized to the segment length. The observed differences in the size variability can be interpreted as muscle-related differences in hypertrophic responsiveness to resistance training. The muscle-dependent size variability may be related to the differences in the fiber-type composition and/or muscle usage in daily life among examined muscle groups.
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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 | 0.002 |
| 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".