Effect of a Core Stabilization Training Program on Performance of Ballet and Modern Dancers
Bibliographic record
Abstract
Kalaycioglu, T, Apostolopoulos, NC, Goldere, S, Duger, T, and Baltaci, G. Effect of a core stabilization training program on performance of ballet and modern dancers. J Strength Cond Res 34(4): 1166-1175, 2020-The aim of this study was to investigate the effects of a core stabilization training (CST) program on performance of university-level ballet and modern dancers. Twenty-four dancers between the ages of 18 and 24 years participated in the study. Core stabilization training was performed for 45-60 minutes per day, 3 days a week, for 8 weeks. For 2 days, the training was conducted by an experienced physiotherapist, and the other day, each participant exercised on his or her own. Evaluation of physical fitness parameters included vertical jump performance, flexibility, dynamic balance, coordination, proprioception, muscle, and hip flexion isokinetic strength measures. Wilcoxon signed rank test was used to compare pre- and post-test values. Statistically significant increases in vertical jump performance, dynamic balance, proprioception, and coordination parameters between pre- and post-training (p < 0.05) were observed. After the CST program, peak torque values for the hip flexor muscle isokinetic test of the dancers decreased (p < 0.05). Therefore, the results suggest that the CST program might be used to improve several physical fitness parameters such as jumping, proprioception, coordination, and dynamic balance. Such improvements will aid in the development of artistic skills for university modern dancers.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.002 | 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".