Bibliographic record
Abstract
Resistance exercise training (RET) can lead to muscle hypertrophy; however, the relative contribution that exogenous (protein supplementation and specific training variables) versus endogenous (biology inherent to the individual) factors have on RET-induced muscle hypertrophy is controversial. In Study 1, we provided an evidence-based conclusion that protein supplementation during periods of RET results in a small but statistically significant increase in RET-induced muscle hypertrophy. In Study 2, we corroborate previous research and observed that the amount of mass lifted per repetition (load) did not determine RET-induced muscle hypertrophy in resistance-trained men when RET was performed to volitional fatigue. In Study 4, we observed similar muscle fibre activation following resistance exercise with lighter versus heavier loads when both were lifted until volitional fatigue. In Studies 2 and 3, we observed no relationship between circulating anabolic hormones (e.g., testosterone) and RET-induced muscle hypertrophy. Nonetheless, in Study 3, we found significantly greater muscle androgen receptor content in the top versus the bottom quintile of respondents for muscle hypertrophy following 12 weeks of RET indicating that androgen receptor content, and not circulating androgen concentration, may be an important determinant of hypertrophy. Finally, in Study 5, we observed that RET-induced muscle hypertrophy was an consistent within an individual (independent of load and limb) but considerably different between participants. Together, these data suggest that the exogenous factors we studied – protein supplementation and load (when RET was performed to volitional fatigue) – had a relatively small influence on RET-induced muscle hypertrophy. In contrast, we found that endogenous variables, such as intramuscular androgen receptor content and likely other genetic influences, appear to contribute more to the significant heterogeneity seen in RET-induced muscle hypertrophy. Future research in this area should prioritize understanding the biology that underpins the individual variability in RET-induced muscle hypertrophy.
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How this classification was reachedexpand
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) | 0.001 | 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) | 0.060 | 0.001 |
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; both teacher heads agree on what is shown here.
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".