Nitrate Supplementation’s Improvement of 10-km Time-Trial Performance in Trained Cyclists
Bibliographic record
Abstract
Six days of dietary nitrate supplementation in the form of beetroot juice (~0.5 L/d) has been reported to reduce pulmonary oxygen uptake (VO₂) during submaximal exercise and increase tolerance of high-intensity work rates, suggesting that nitrate can be a potent ergogenic aid. Limited data are available regarding the effect of nitrate ingestion on athletic performance, and no study has investigated the potential ergogenic effects of a small-volume, concentrated dose of beetroot juice. The authors tested the hypothesis that 6 d of nitrate ingestion would improve time-trial performance in trained cyclists. Using a double-blind, repeated-measures crossover design, 12 male cyclists (31±3 yr, VO2peak=58±2 ml·kg⁻¹·min⁻¹, maximal power [Wmax]=342±10 W) ingested 140 ml/d of concentrated beetroot (~8 mmol/d nitrate) juice (BEET) or a placebo (nitrate-depleted beetroot juice; PLAC) for 6 d, separated by a 14-d washout. After supplementation on Day 6, subjects performed 60 min of submaximal cycling (2×30 min at 45% and 65% Wmax, respectively), followed by a 10-km time trial. Time-trial performance (953±18 vs. 965±18 s, p<.005) and power output (294±12 vs. 288±12 W, p<.05) improved after BEET compared with PLAC supplementation. Submaximal VO₂ was lower after BEET (45% Wmax=1.92±0.06 vs. 2.02±0.09 L/min, 65% Wmax 2.94±0.12 vs. 3.11±0.12 L/min) than with PLAC (main effect, p<.05). Whole-body fuel selection and plasma lactate, glucose, and insulin concentrations did not differ between treatments. Six days of nitrate supplementation reduced VO₂ during submaximal exercise and improved time-trial performance in trained cyclists.
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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 | 0.000 |
| 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".