Effect of beetroot juice supplementation on 10-km performance in recreational runners
Bibliographic record
Abstract
The purpose of this study was to investigate the effects of chronic beetroot juice (BRJ) supplementation on 10-km running performance in recreational runners. In a double-blind, placebo-controlled, crossover-designed study, 14 male recreational runners (age, 27.8 ± 3.4 years) performed three 10-km running tests, at baseline and under the conditions of BRJ supplementation and placebo (PLA). Supplementation was administered for 3 days, and on the days of the assessments, the ingestion occurred 2 h before the test and consisted of a dose of 420 mL of BRJ in natura (8.4 mmol inorganic nitrate (NO3−)·day−1) or PLA with depleted NO3− (0.01 mmol NO3−·day−1). The mean velocity (MV) was calculated, and the following variables were determined: maximal heart rate, maximal rating of perceived exertion, blood glucose concentration (analyzed before and after the test), and lactate peak. There was no main effect between conditions regarding 10-km running time performance (BRJ: 50.1 ± 5.3 min; PLA: 51.0 ± 5.1 min; P = 0.391) and total MV (BRJ: 12.1 ± 1.3 km·h−1; PLA: 11.9 ± 1.2 km·h−1; P = 0.321) or in the other analyzed variables. The time to complete the first half of the test (5 km) was statistically lower in the BRJ group than in the PLA group (P = 0.027). In conclusion, chronic supplementation with BRJ increased MV in the first half of the test and improved the final test times of 10 of the 14 runners, although we did not find a statistically significant difference in the performance of the 10-km run.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 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".