Acute Effect of Whole-Body Vibration on Sprint and Jumping Performance in Elite Skeleton Athletes
Bibliographic record
Abstract
The winter sliding sport known as skeleton requires athletes to produce a maximal sprint followed by high speed sliding down a bobsled track. Athletes are required to complete the course twice in 1 hour and total time for the 2 runs determines overall ranking. The purpose of this investigation was to examine the effect of whole-body vibration (WBV) on lower body power to explore the utility of WBV as an ergogenic aid for skeleton competition. Elite skeleton athletes (1 male and 6 females) completed an unloaded squat jump (SQJ) immediately followed by 2 countermovement jumps (CMJs) and a maximal 30-m sprint before and after WBV or no vibration (CON) using a crossover design. The second 30-m sprint was slower following both CON (1.4% decrement; p = 0.05) and WBV (0.7% decrement; p = 0.03). Mean vertical velocity was maintained following WBV in the SQJ but decreased following CON (p = 0.03). There was a trend for athletes to commence the SQJ from a higher starting stance post-WBV compared to CON (p = 0.08). WBV decreased total vertical distance traveled compared to CON in the SQJ (p = 0.006). WBV had little effect on peak velocity, jump height, dip, and peak acceleration or any CMJ parameters. When sprint athletes' warm up and perform maximal jumps and a 30-m sprint with 15-20 minutes of recovery before repeating the sequence, the second series of performances tend to be compromised. However, when WBV is used before the second series of efforts, some aspects of maximal jumping and sprinting appear to be influenced in a beneficial manner. Further research is required to explore whether WBV can improve the second sprint for athletes in actual competition and/or what sort of WBV protocol is optimal for these populations.
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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 | 0.000 | 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) | 0.001 | 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".