The Electromyographic Threshold in Girls and Women
Bibliographic record
Abstract
Background: The electromyographic threshold (EMGTh) is thought to reflect increased high-threshold/type-II motor-unit (MU) recruitment and was shown higher in boys than in men. Women differ from men in muscular function. Purpose: Establish whether females’ EMGTh and girls–women differences are different than males’. Methods: Nineteen women (22.9 ± 3.3yrs) and 20 girls (10.3 ± 1.1yrs) had surface EMG recorded from the right and left vastus lateralis muscles during ramped cycle-ergometry to exhaustion. EMG root-mean-squares were averaged per pedal revolution. EMGTh was determined as the least residual sum of squares for any two regression-line data divisions, if the trace rose ≥ 3SD above its regression line. EMGTh was expressed as % final power-output (%Pmax) and %VO2pk power (%PVO2pk). Results: EMGTh was detected in 13 (68%) of women, but only 9 (45%) of girls (p < .005) and tended to be higher in the girls (%Pmax= 88.6 ± 7.0 vs. 83.0 ± 6.9%, p = .080; %PVO2pk= (101.6 ± 17.6 vs. 90.6 ± 7.8%, p = .063). When EMGTh was undetected it was assumed to occur at 100%Pmax or beyond. Consequently, EMGTh values turned significantly higher in girls than in women (94.8 ± 7.4 vs. 88.4 ± 9.9%Pmax, p = .026; and 103.2 ± 11.7 vs. 95.2 ± 9.9%PVO2pk, p = .028). Conclusions: During progressive exercise, girls appear to rely less on higher-threshold/type-II MUs than do women, suggesting differential muscle activation strategy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".