[Traducción al español] Funciones cognitivas y su relación con el equilibrio y la agilidad en atletas de diferentes ramas deportivas
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Bibliographic record
Abstract
Successful performance in each sport requires high ability in various features, including motor and perceptual-cognitive skills. The aim of this study was to compare balance and agility in athletes from several sports branches in order to find out how cognitive functions relate to these parameters. Seventy-three individuals aged 18-30 were included in this prospective-descriptive study. In the assessment of cognition, Montreal Cognitive Assessment Scale, d2 Test of Attention, and a Bassin Anticipation Timer Device were used. While Prokin-TecnoBody was used to measure the balance skills, Illinois Agility Test (IAT) was used for agility. IAT times showed positive weak correlations with both the absolute error-score (AES) at 8mph (r=0.260, p=0.040) and mediolateral balance score (ML)(r=0.255, p=0.043). While there was a negative weak correlation between AES at 3mph and anteroposterior score of balance (r=-0.267, p=0.035), we found positive weak correlation between AES at 8mph and ML of balance (r=0.253, p=0.046). It was found that the IAT scores of the inactive group were significantly lower than those of athletes (p=0.000). According to AES at 3mph, there were significant differences between tennis players and both inactive and volleyball players (p=0.008, p=0.002, respectively). When the AES at 8mph was compared, the only statistically significant difference was between tennis players and inactive (p=0.008). In conclusion, this study shows how cognitive functions, particularly coincidence anticipation timing (CAT), correlate with essential physical performance factors like agility and balance across different sport branches, suggesting that improving cognitive skills could enhance overall athletic performance and inform mental training strategies in sports. It is recommended that future sports science research focus on enhancing CAT through targeted training programs.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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 it