The effects of long muscle length isometric versus full range of motion isotonic training on regional quadriceps femoris hypertrophy in resistance-trained individuals
Bibliographic record
Abstract
This study explored the effects of isometric training at long muscle lengths (ISOM) versus full range of motion isotonic training (ISOT) on quadriceps femoris regional hypertrophy. Twenty-three healthy, resistance-trained men and women completed a 6-week, twice-per-week intervention. A within-subject study design was employed with limbs randomized to unilateral ISOM or ISOT knee extension. Muscle thickness was assessed pre- and post-intervention at proximal, middle, and distal sites of the anterior thigh and lateral thigh. Data was analyzed using Bayesian linear mixed-effects models. The between-condition estimate for summed anterior thigh muscle thickness was -0.20 cm (high-density credible intervals (HDI): -0.54, 0.16), with 87% probability of direction (pd), and 75% of the posterior distribution exceeding the region of practical equivalence (ROPE). At the proximal site of the anterior thigh, between-condition estimates showed the greatest directional shift in favor of ISOM (contrast estimate: -0.11 cm (95% HDI: -0.24, 0.02)), with 82% of the posterior distribution exceeding the ROPE. Minimal to negligible changes in summed and regional lateral thigh muscle thickness were found for both conditions. Overall, ISOM and ISOT elicited similar quadriceps hypertrophy in resistance-trained individuals. Isometric training at long muscle lengths may elicit a superior hypertrophic effect in the proximal anterior thigh; however, uncertainty in the effect estimates precludes definitive conclusion in this regard and further investigation is warranted.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 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".