RELIABILITY OF A NEW MEASURE OF MOTONEURON EXCITABILITY
Bibliographic record
Abstract
PURPOSE This study examined the reliability of a new measure of motoneuron excitability. METHODS The slope of the regression line of the Hoffmann-reflex stimulus-response (SR) curve advocated by Funase et al. (1994) was compared to the peak of the first derivative of the H-reflex SR curve (dH/dVmax), the new measure introduced in the research. The H-reflex amplitude at 5% of the maximum M-wave (Mmax) is an established measure, and was used as another basis for comparison. The soleus H-reflex was elicited in 24 subjects on five separate days. Vibration was applied to the Achilles tendon to test the sensitivity of the measures on test day four. The means of five evoked potentials at each gradually increasing intensity, from below H-reflex threshold to above Mmax, were used to create both the H-reflex and M-wave SR curves for each subject across test days. RESULTS There was a modest decrease in all H-reflex measures from the first to third test day, but it was non-significant (P's > 0.05). All measures of the H-reflex exhibited a profound reduction following vibration on test day four, and then return to baseline levels on test day five (P's < 0.05). The intraclass correlation coefficient (ICC) for H-reflex amplitude at 5% of Mmax was 0.65. The ICC for the slope of the regression line was 0.65 while it was 0.73 for dH/dVmax. CONCLUSIONS The peak of the first derivative of the H-reflex SR curve (dH/dVmax) was therefore shown to have comparable reliability and sensitivity to other more established measures.
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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 | 0.007 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".