Examination of Physical Fitness and Somatotype Features of Parkour Practitioners (Traceur) and Gymnasts in University Education
Bibliographic record
Abstract
The purpose of this study was to examination the physical and anthropometric features of the traceurs with the gymnasts university education. The study was carried out with university students, male twelve volunteer participants (traceurs=6, gymnasts=6). The mean age of the traceurs was 18.67±1.03 years, 172.67±3.78 cm, body weight 62.5±8.94 kg and BMI was 20.98±2.97 kg/m2; gymnasts was 19.33±1.21 years, 175.83±6.18 cm, body weight 65.17±8.06 kg and BMI was 21.11±2.67 kg/m2. According to the data obtained from traceurs and gymnasts, the somatotype features of the athletes were endomorph (2.70±0.32), mesomorph (4.09±1.70) and ectomorph (3.39±1.67), and endomorph (2.90±0.48), mesomorph (3.83±1.51) and ectomorph (3.49±1.52), respectively. It can be said that the dominant somatotype structures between the groups and within the groups are mesomorphy and ectomorphy in the traceurs and gymnasts. When somatotype features were compared between groups, no significant difference was observed. It is noteworthy that both branches have similar body structures (mesomorphy and ectomorphy). In conclusion, learning of these body structure features that determine and affect the performance by coaches education of athletes that athletes will show that perform successfully only with appropriate body structures and coaches may enable the preparation of a better training program.
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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) | 0.003 | 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".