Influence of needle electrode depth on DE‐STA motor unit number estimation
Bibliographic record
Abstract
INTRODUCTION: To assess a potential source of technique-associated error, we evaluated the influence of needle electrode depth on decomposition-enhanced spike-triggered averaging (DE-STA) motor unit number estimation (MUNE) and quantitative motor unit analysis in the upper trapezius (UT). METHODS: The DE-STA MUNE protocol was performed at superficial, intermediate, and deep needle electrode depths in 18 control subjects. RESULTS: Mean surface-detected motor unit potential amplitudes were significantly smaller for intermediate versus superficial (P<0.05), deep versus superficial (P<0.001), and deep versus intermediate (P<0.05). MUNE was significantly larger for deep versus superficial (P<0.001), with statistical trends toward larger MUNE values at greater depths for the remaining comparisons. No significant differences were found among needle electrode depths for quantitative motor unit potential parameters. CONCLUSIONS: These results demonstrate the important influence of needle electrode depth on DE-STA MUNE in the UT. Suggestions are made for improved standardization of the protocol.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".