Energy drinks do not alter aerobic fitness assessment using field tests in healthy adults regardless of physical fitness status
Bibliographic record
Abstract
Purpose: The purpose of this study was to evaluate the effects of energy drink ingestion on the performance of running performance in amateur runners with different levels of physical fitness.Material: Sixty healthy subjects were selected and randomized according to the level of physical fitness (Low: <29.9 ml.kg -1 .min-1 ; Moderate: 30-37.9ml.kg -1 .min-1 ; and High: > 38 ml.kg -1 .min-1 ).Thereafter, they were further distributed in Placebo (27g glucose) and Energy Drink (27g glucose, 30g sodium, 1000mg taurine, 600mg glucuronolactone, 80mg caffeine, 50mg inositol, 16mg vitamin B3, 5mg vitamin B5, 1,3mg vitamin B2, 3 mg vitamin B6 and 2.4 mg vitamin B12), resulting in six groups according to physical fitness level such Placebo (P, Low: L, Moderate: M, High: H) and Energy Drink (ED, Low: L, Moderate: M, High: H).The drinks were administered 60 minutes prior to the cooper test.Results: Energy drink ingestion did not elicit performance improvement despite physical fitness level.However, the L group running distance was longer (P:3168 ± 167; ED: 3228 ± 218, meters) than M (P:1962 ± 75; ED: 2035 ± 105, meters) and L (P: 1422 ± 74; ED: 1440 ± 62, meters) (p<0.01).The same result was found following the use of the equation for calculating oxygen consumption (L group P: 20±1.4;BE: 23±1.4;ml.kg -1 .min-1 ; M group P: 35±1.0;BE: 34±0.9 ml.kg -1 .min-1 ; and H group P: 54±3.7;ED: 60±4.8 ml.kg - 1 .min-1 ).Conclusion: Data from the present study demonstrated that the use of energy drinks does not enhance performance of amateur runners regardless of the level of 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) | 0.000 | 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".