Prolonged passive static stretching-induced innervation zone shift in biceps brachii
Bibliographic record
Abstract
The purpose of this study was to examine the influence of a bout of repeated and prolonged passive static stretching on the innervation zone (IZ) location of the human biceps brachii muscle. Eleven men performed 12 sets of 100-s passive stretches on their biceps brachii. Before (Pre) and immediately after (Post) the stretching intervention, isometric strength was tested during the maximal voluntary contractions (MVCs) of the forearm flexors. The subjects also performed several separate isometric forearm flexion muscle actions at 30%, 50%, and 70% of their predetermined MVCs for examining the locations of the IZ at different contraction intensities. The IZ was identified through multi-channel surface electromyographic (EMG) recordings from a linear electrode array. The stretching intervention induced an average of 10% isometric strength loss for the forearm flexors (mean±SD: Pre-MVC vs. Post-MVC=332.12±59.40 N vs. 299.53±70.51 N; p<0.001). In addition, the average IZ shift was nearly 4.5 mm in average in the proximal direction. However, this shift was not specific to the contraction intensity. We believe that the IZ shift was caused by the elongation of the entire muscle-tendon unit in the proximal direction. Therefore, caution should be taken when using surface EMG technique to examine possible changes in the EMG variables after a stretching protocol, as these variables can be contaminated by the shift of the IZ.
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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 | 0.001 |
| 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) | 0.001 | 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".