Near-Fibre Electromyography
Bibliographic record
Abstract
Abstract Near fibre electromyography (NFEMG) is the use of specifically high-pass filtered motor unit potential (MUPs) (i.e. near fibre MUPs (NFMs)) extracted from needle-detected EMG signals for the examination of changes in motor unit (MU) morphology and electrophysiology caused by neuromuscular disorders or ageing. The concepts of NFEMG, the parameters used, including NFM duration and dispersion, which relates to fibre diameter variability and/or endplate scatter, and a new measure of neuromuscular junction transmission (NMJ) instability, NFM segment jitter, and the methods for obtaining their values are explained. Evaluations using simulated needle-detected EMG data and exemplary human data are presented, described and discussed. The data presented demonstrate the ability of using NFEMG parameters to detect changes in MU fibre diameter variability, end plate scatter, and neuromuscular transmission time variability. These changes can be detected prior to alterations of MU size, numbers or muscle recruitment patterns.
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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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".