Anconeus motor unit number estimates using decomposition‐based quantitative electromyography
Bibliographic record
Abstract
INTRODUCTION: Motor unit number estimates (MUNEs) provide important information in health, aging, and disease, and can be determined using decomposition-enhanced spike-triggered averaging (DE-STA). Discrimination of surface-detected motor unit potentials (S-MUPs) has been limited to contractile forces of ∽30% maximum voluntary contraction (MVC), which is insufficient to recruit a representative sample of the entire MU pool in most muscles. Unique features of the anconeus may permit MUNEs at high muscle activation levels. METHODS: In 10 men (25 ± 3 years), anconeus MUNEs were performed using DE-STA at 10%, 30%, and 50% root-mean-square of MVC (RMS(MVC)). RESULTS: The mean compound muscle action potential of the anconeus was ∽6 mV, and average S-MUP amplitudes were ∽100 μV, 145 μV, and 235 μV at 10%, 30%, and 50% RMS(MVC), resulting in low average MUNEs of 58, 38, and 25, respectively. CONCLUSIONS: Elbow extensor force-EMG relationships suggest full recruitment of the anconeus MU pool at 50% RMS(MVC), thus providing a representative sample for MUNE.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".