The probability density function of vibromyographic and electromyographic signals for different levels of contraction of human quadriceps muscles
Bibliographic record
Abstract
The probability density function (pdf) of random vibromyographic (VMG) and electromyographic (EMG) signals were studied. VMG and EMG signals were obtained from the quadriceps muscles of four subjects contracting at 20%, 40%, 60%, 80% and 100% of maximum voluntary contraction (MVC) at knee angles of 30/spl deg/, 60/spl deg/ and 90/spl deg/. Levels of contraction were controlled using the torque reading of a Cybex II dynamometer. Histograms of the VMG and EMG signals at different levels of contraction were made. Using Pearson's /spl chi//sup 2/-test, the goodness of fit to a Gaussian distribution was calculated for the VMG and EMG signals obtained from rectus femoris. The pdf of the VMG and EMG roughly approximated a Gaussian distribution, but both signals were found to be statistically different from a Gaussian distribution using Pearson's /spl chi//sup 2/ test. The goodness of fit of the pdf of the VMG and EMG signals to a Gaussian distribution were calculated.>
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.001 |
| 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".