Effect of Sugar-Free Red Bull Energy Drink on High-Intensity Run Time-to-Exhaustion in Young Adults
Bibliographic record
Abstract
Consuming sugar-free Red Bull energy drink before exercise has become increasingly popular among exercising individuals. The main purported active ingredient in sugar-free Red Bull is caffeine, which has been shown to increase aerobic exercise performance. The purpose of this study was to determine the effects of sugar-free Red Bull energy drink on high-intensity run time-to-exhaustion in young adults. Physically active university students (n = 17, 9 men, 8 woman; 21 +/- 4 years, 73.4 +/- 3.1 kg, 175.1 +/- 3.2 cm) participated in a double-blind, crossover, repeated-measures study where they were randomized to supplement with sugar-free Red Bull (2 mg x kg(-1) body mass caffeine or approximately 147 mg caffeine; 4 kcal/250 mL) and noncaffeinated, sugar-free placebo (lemon-lime flavored soft drink, tonic water, lime juice; 4 kcal/250 mL) separated by 7 days. Exercise capacity was assessed by a run time-to-exhaustion test at 80% Vo2max, perceived exertion was assessed immediately after exercise, and blood lactate was measured before and after exercise. There were no differences in run time-to-exhaustion (Red Bull: 12.6 +/- 3.8 minutes, placebo: 11.8 +/- 3.4 minutes), perceived exertion (Red Bull: 17.1 +/- 2.0, placebo: 16.6 +/- 1.8), or blood lactate between groups. In conclusion, sugar-free Red Bull energy drink did not influence high-intensity run time-to-exhaustion in young adults.
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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) | 0.001 | 0.001 |
| 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 | 0.001 | 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".