Effect of a Six-Week Preparation Period on Acute Physiological Responses to a Simulated Combat in Young National-Level Taekwondo Athletes
Bibliographic record
Abstract
The aim of this study was to examine changes in physical attributes, physiological characteristics and responses that occurred in a simulated combat during a six-week preparatory period in young taekwondo athletes. Seven athletes (age 12.17 ± 1.11 years) were examined before (pre-intervention) and after (post-intervention) a preparatory period for physical fitness and physiological responses to a 2×90 s simulated bout with a 30 s rest period. The heart rate (HR) was monitored during the simulated combat, and handgrip muscle strength (HMS) along with the countermovement jump (CMJ) were recorded before and after the combat. When compared with pre-intervention values, in post-intervention we observed a decrease in body mass, body fat percentage, and the HR at rest and during recovery after a 3 min step test, and an increase in maximal velocity of the cycle ergometer force-velocity test, the CMJ and mean power during the 30 s continuous jumping test (p<0.05). Furthermore, HR responses to a simulated combat were lower in the post-intervention session (p<0.05). CMJ values increased after the bout in both pre and post-intervention, with higher absolute values in the latter case (p<0.05), whereas there was no difference in HMS. Based on these findings, it can be concluded that the acute physiological responses to a simulated taekwondo combat vary during a season, which might be explained by changes in physical fitness.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".