A Preliminary Study on the Relationship Between Athletes' Ability to Self-Regulate and World Ranking
Bibliographic record
Abstract
This study was designed to explore the relationship between elite athletes' self-regulation ability and their ranking at the world level using psychophysiological stress assessment profiling. Fifteen elite level athletes' psychophysiological stress response patterns were recorded during a nine-stage stress assessment. Respiration rate, heart rate, heart rate variability, skin conductance, peripheral body temperature, and electromyograph (trapezius and frontalis) were monitored. There was a significant correlation between elite athletes' overall self-regulation ability and their ranking at the world level, meaning that the better the overall self-regulation ability of the athlete, the better the world ranking. In addition, a multiple regression analysis indicated that self-regulation accounted for 76% of the variance in world ranking. Our results suggest the existence of a relationship between elite athletes' overall self-regulation ability and their ranking at the world level. Therefore, the results of this study have important implications for training of optimal psychophysiological self-regulation in athletes.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 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".