Examination of Physical and Physiological Parameters of National Level Boxers at Age Range of 11–13
Bibliographic record
Abstract
Delivering successful performance in sports depends on physical fitness. Unless the physical and physiological structure is in accordance with the requirements of the sports branch, a high performance in sports cannot be realized fully (Çakmakçı, 2002). Therefore, it is important to define and improve performance parameters such as body composition, anaerobic-aerobic endurance, capacity and strength in boxing. Accordingly, In this study, it is aimed to examine the physical and physiological fitness parameters of tiny natioanal boxers between 11–13 years of age. The research was carried out on 12 boxing athletes between 11–13 years of age in the tiny national category in Kırıkkale province. In statistical analysis, normality was understood by Shapiro-Wilk test and descriptive statistics method was used to define the data. In this study, maximum oxygen consumption capacity (VO2) maxs, lung functional volumes, hand grip strength levels and body composition measurements of boxing athletes were evaluated. The mean of (VO2) max values of the participants were measured 44.17 ± 8.45. Also in correlation analysis, a high relationship was found at (VO2) max BMR; r = -750, p = 0.01 level between maximal oxygen consumption capacity and basal metabolic rate However, in oxygen consumption capacity and body composition variables, The negatively significant level relationships were found at levels of (VO2) max; body fat percentage (FM), r = -696, p = 0.05, lean body mass (FFM), r = -666, p = 0.05; body mass index (BMI), r = -763, p = 0.01). As a result, in this study, identification and relationship were determined about performance data in physical and physiological fitness parameters of tiny elite boxing athletes and a data about this age group was created in boxing athletes for future studies.
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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 | 0.001 | 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) | 0.004 | 0.001 |
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".