A New Method for Experimental Simulation of EMG Using Multi-Channel Independent Stimulation of Small Groups of Motor Units
Bibliographic record
Abstract
The experimental simulation method was based upon the separate activation of up to 10 small groups of motor units (MU) in an acute nerve-muscle preparation. The investigator was able to precisely control and systematically alter the features of MU pool activation strategies. No implicit assumptions were made regarding MU properties. The purpose of this study was to evaluate the validity of this method. Three criteria were formulated and found to be satisfied: First, in the time domain, visual and audio displays of simulated EMG were indistinguishable from physiological EMG. Secondly, in the frequency domain, power spectra of simulated EMG revealed the typical features of EMG recorded during voluntary activation in the cat. Thirdly, the well-known monotonic relationship between EMG magnitude and force was readily reproduced, although strictly linear relations were not found. In addition, the relationship between the pool's ensemble activation rate and EMG magnitude showed distinct gain compression, mostly attributable to signal cancellation.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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; 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".