Beetroot juice does not enhance altitude running performance in well-trained athletes
Bibliographic record
Abstract
We hypothesized that acute dietary nitrate (NO3(-)) provided as concentrated beetroot juice supplement would improve endurance running performance of well-trained runners in normobaric hypoxia. Ten male runners (mean (SD): sea level maximal oxygen uptake, 66 (7) mL·kg(-1)·min(-1); 10 km personal best, 36 (2) min) completed incremental exercise to exhaustion at 4000 m and a 10-km treadmill time-trial at 2500 m simulated altitude on separate days after supplementation with ∼7 mmol NO3(-) and a placebo at 2.5 h before exercise. Oxygen cost, arterial oxygen saturation, heart rate, and ratings of perceived exertion (RPE) were determined during the incremental exercise test. Differences between treatments were determined using means [95% confidence intervals], paired sample t tests, and a probability of individual response analysis. NO3(-) supplementation increased plasma nitrite concentration (NO3(-), 473 (226) nmol·L(-1) vs. placebo, 61 (37) nmol·L(-1), P < 0.001) but did not alter time to exhaustion during the incremental test (NO3(-), 402 (80) s vs. placebo 393 (62) s, P = 0.5) or time to complete the 10-km time-trial (NO3(-), 2862 (233) s vs. placebo, 2874 (265) s, P = 0.6). Further, no practically meaningful beneficial effect on time-trial performance was observed as the 11 [-60 to 38] s improvement was less than the a priori determined minimum important difference (51 s), and only 3 runners experienced a "likely, probable" performance improvement. NO3(-) also did not alter oxygen cost, arterial oxygen saturation, heart rate, or RPE. Acute dietary NO3(-) supplementation did not consistently enhance running performance of well-trained athletes in normobaric hypoxia.
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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) | 0.000 | 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) | 0.001 | 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".