Nitrate Supplementation’s Improvement of 10-km Time-Trial Performance in Trained Cyclists
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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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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it