Improving the measurement of TMS-assessed voluntary activation in the knee extensors
Bibliographic record
Abstract
The present study was designed to test the accuracy, validity, reliability and sensitivity of the main outcomes of alternative methods for the measure of TMS-assessed voluntary activation (VATMS) in the knee extensors. Ten healthy recreationally active males (24 ± 5 years) completed a neuromuscular assessment protocol (NMA) before and immediately after a fatiguing isometric exercise, consisting of two sets of five contractions (50%, 62.5%, 75%, 87.5%, and 100% of Maximal Voluntary Contraction; MVC) with superimposed TMS-evoked twitches (SITs) for calculation of VATMS (1x5C vs. 2x5C). The protocol was performed on two separate occasions for the measurement of between-day reliability. Where deemed appropriate, comparisons were made with a routinely used protocol [i.e. 50%, 75%, and 100% of MVC (1x3C) performed three times (3x3C)] from re-analysed data (Dekerle et al., 2018). Confidence intervals for the measure of a key determinant of VATMS (estimated resting twitch) were similar between 1x5C and 2x5C but improved by six-fold when compared to 1x3C (P<0.05). Potentiated twitch force evoked via percutaneous electrical stimulation of the femoral nerve was unchanged from pre- to post-NMA at baseline for 1x5C (P>0.05) but decreased for 2x5C and 3x3C (P<0.05). Its recovery post-exercise was lesser for 1x5C compared to 2x5C and 3x3C (P<0.05), with no difference between the latter two (P>0.05). Absolute reliability was strong enough for both 1x5C and 2x5C to depict a true detectable change in the sample’s VATMS following the fatiguing exercise (TEM < 3% at rest, <9% post-exercise) but 2x5C was marginally more sensitive to individual’s changes at baseline. In conclusion, both 1x5C and 2x5C provide reliable measures of VATMS. However, the 1x5C protocol may hold stronger internal validity.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".