Core Stability and Electromyographic Activity of the Trunk Musculature in Different Woman’s Sports
Bibliographic record
Abstract
Volleyball players and gymnasts need strength training to achieve their optimum sport performance. The aims of this study were to describe body composition, strength, performance, and characteristics of trunk muscle activation in volleyball players and gymnasts, and to analyze the differences between the sports. The sample consisted of 40 female athletes: rhythmic gymnasts (n = 24; age 13.95 ± 2.77 years) and volleyball players (n = 16; age 19.81 ± 5.55 years). Body composition, maximum voluntary contraction (MVC) of isometric tests in an isokinetic dynamometer, McGill core endurance test, and surface electromyography (EMGrms) of the trunk muscle during the McGill test and isometric tests were recorded. Rhythmic gymnasts presented lower body composition values than volleyball players (p < 0.05). The volleyball players presented higher isometric strength than rhythmic gymnasts in terms of MVC in trunk flexion (p < 0.05, d = 1.3) and trunk extension (p < 0.001, d = 1.3). EMGrms from the rhythmic gymnasts were greater for trunk flexor muscles (p < 0.01, d = 0.7) and trunk extensor muscles (p < 0.001, d = 1.3) during McGill endurance tests compared to the volleyball players. In the isometric test, EMGrms from the rhythmic gymnasts were greater for trunk flexor muscles in flexion (p < 0.01, d = 0.9) and extension tests (p < 0.05, d = 0.7). In conclusion, the volleyball players exhibited higher peak strength, despite the fact that the gymnasts showed greater muscle activity during the maximum voluntary contraction.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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) | 0.002 | 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".