Comparison of Explosive Strength and Anaerobic Power Performance of Taekwondo and Karate Athletes
Bibliographic record
Abstract
The aim of this study is to compare explosive strength and anaerobic power performance of taekwondo and karate athletes. 10 taekwondo and 10 karate athletes participated to the study voluntarily by taking “Informed Consent Form”. The athletes’ values were in taekwondo as mean of age 21±2.4 years, height 181.2±8.01 cm, weight 66.9±15.74 kg, sport age 7.5±5.52 years; in karate as mean of age 21.1±1.66 years, height 170.2±10.04 cm, weight 64.4±15.69 kg, sport age 10.5±3.83 years. Counter movement jump, standing long jump and Wingate Anaerobic Test were applied to the athletes. The data were analyzed by using statistical package program. Descriptive statistics were used for mean and standard deviation values, “Shapiro-Wilk” test was used to determine whether the data showed normal distribution or not and “Independent t Test” was used for comparisons. The results were evaluated according to “p<0.05” significance level. According to Independent t Test’s results of vertical and standing long jump tests, there were statistically significant differences in both vertical jump and standing long jump test averages of athletes (p<0.05). In comparison Wingate anaerobic test, significant differences were found in “Watt” values of groups’ Peak, Average and Minimum Power (p<0.05). In “kg/Watt” values of groups’, differences were found statistically significant in Peak and Minimum Power (p<0.05), while differences were not found significant in Average Power (p>0.05). As a result, when explosive strength and anaerobic power characteristics of taekwondo and karate athletes were compared, a difference was found between the two branches. The reason for this can be said to be different competition times, training programs, training methods and physical requirements of the branches. In addition, taekwondo athletes foot techniques, karate athletes using hand techniques more than foot techniques can be listed as the reasons for this difference.
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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 | 0.001 | 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) | 0.002 | 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".