A noninvasive test for estimating myosin heavy chain of the vastus lateralis in females with mechanomyography
Bibliographic record
Abstract
This study examined relationships between percent myosin heavy chain (%MHC) expression and mechanomyographic amplitude (MMGRMS). Fifteen females (age ± SD=21.3 ± 5.3 yrs) completed isometric trapezoidal contractions at 30% and 70% maximal voluntary contraction (MVC). MMG was recorded from the vastus lateralis (VL). Participants gave a muscle biopsy of the VL post-testing. MMGRMS-torque relationships during the linearly varying segments were log-transformed and linear regressions were applied to calculate b terms (slopes). For the steady torque segment, MMGRMS was averaged. Correlations were performed for type I%MHC with the MMG variables. Multiple regression was utilized to examine prediction equations for type I%MHC. Type I%MHC was significantly correlated with the b terms during the increasing segment of the 70% MVC (p = 0.003; r = -0.718), and MMGRMS during steady torque at 30% (p = 0.008; r = -0.652) and 70% MVC (p = 0.040; r = -0.535). Type I%MHC reduced the linearity of the MMGRMS-torque relationship during the high-intensity linearly increasing segment, and MMGRMS at a low- and high-intensity steady torque. A combination of MMG variables estimated type I%MHC expression with 81.2% accuracy. MMG recorded during a low- and high-intensity isometric trapezoidal contraction may offer a simple, noninvasive test for estimating type I%MHC expression of the VL in sedentary females.
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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) | 0.000 | 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".