Resistance Training Recommendations to Maximize Muscle Hypertrophy in an Athletic Population: Position Stand of the IUSCA
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Hypertrophy can be operationally defined as an increase in the axial cross-sectional area of a muscle fiber or whole muscle, and is due to increases in the size of pre-existing muscle fibers. Hypertrophy is a desired outcome in many sports. For some athletes, muscular bulk and, conceivably, the accompanying increase in strength/power, are desirable attributes for optimal performance. Moreover, bodybuilders and other physique athletes are judged in part on their muscular size, with placings predicated on the overall magnitude of lean mass. In some cases, even relatively small improvements in hypertrophy might be the difference between winning and losing in competition for these athletes. This position stand of leading experts in the field synthesizes the current body of research to provide guidelines for maximizing skeletal muscle hypertrophy in an athletic population. The recommendations represent a consensus of a consortium of experts in the field, based on the best available current evidence. Specific sections of the paper are devoted to elucidating the constructs of hypertrophy, reconciliation of acute vs long-term evidence, and the relationship between strength and hypertrophy to provide context to our recommendations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it