The day-to-day reliability of residual force enhancement during voluntary and electrically stimulated contractions
Bibliographic record
Abstract
Residual force enhancement (rFE) is characterized by increased steady-state isometric force following active muscle lengthening compared with a fixed-end isometric contraction at the same muscle length and level of neuromuscular activation. Many studies have characterized rFE in humans; however, the day-to-day reliability of rFE is unclear. We aimed to examine day-to-day reliability of rFE across various contraction types in the dorsiflexors in males and females. Twenty-five recreationally active young adults completed two visits, 1 week apart. Following determination of maximum voluntary contraction (MVC) strength, rFE was assessed during maximal voluntary effort, 20% MVC electrically stimulated, and 20% MVC torque-matching conditions. Each rFE condition was completed at two joint excursions: 0°–20° plantar flexion (PF) and 0°–40° PF. Intraclass correlation coefficients (ICC) assessed relative reliability and typical error of measurement (TEM), and the correlation variability of TEM (CVTEM) assessed absolute reliability. Electrically stimulated contractions demonstrated the highest reliability at 40° PF (ICC: 0.9; CVTEM: 22.8%) and 20° PF (ICC: 0.8; CVTEM: 34.3%), followed by maximal voluntary contractions at 40° PF (ICC: 0.7; CVTEM: 55.1%) and 20° PF (ICC: 0.1; CVTEM: 81.1%). The torque-matching trials showed poor reliability for 20° and 40° PF (ICC: −0.1 to 0.3; CVTEM: 118.1%–155.2%). Our results demonstrate higher reliability of rFE when stretching to the descending limb of the torque–angle relationship compared with the plateau region, and in electrically stimulated compared with voluntary contractions in the dorsiflexors for both males and females.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".