Warm-Up Intensity Does Not Affect the Ergogenic Effect of Sodium Bicarbonate in Adult Men
Bibliographic record
Abstract
This study determined the influence of a high- (HI) versus low-intensity (LI) cycling warm-up on blood acid-base responses and exercise capacity following ingestion of sodium bicarbonate (SB; 0.3 g/kg body mass) or a placebo (PLA; maltodextrin) 3 hr prior to warm-up. Twelve men (21 ± 2 years, 79.2 ± 3.6 kg body mass, and maximum power output [Wmax] 318 ± 36 W) completed a familiarization and four double-blind trials in a counterbalanced order: HI warm-up with SB, HI warm-up with PLA, LI warm-up with SB, and LI warm-up with PLA. LI warm-up was 15 min at 60% Wmax, while the HI warm-up (typical of elites) featured LI followed by 2 × 30 s (3-min break) at Wmax, finishing 30 min prior to a cycling capacity test at 110% Wmax. Blood bicarbonate and lactate were measured throughout. SB supplementation increased blood bicarbonate (+6.4 mmol/L; 95% confidence interval, CI [5.7, 7.1]) prior to greater reductions with HI warm-up (-3.8 mmol/L; 95% CI [-5.8, -1.8]). However, during the 30-min recovery, blood bicarbonate rebounded and increased in all conditions, with concentrations ∼5.3 mmol/L greater with SB supplementation (p < .001). Blood bicarbonate significantly declined during the cycling capacity test at 110%Wmax with greater reductions following SB supplementation (-2.4 mmol/L; 95% CI [-3.8, -0.90]). Aligned with these results, SB supplementation increased total work done during the cycling capacity test at 110% Wmax (+8.5 kJ; 95% CI [3.6, 13.4], ∼19% increase) with no significant main effect of warm-up intensity (+0.0 kJ; 95% CI [-5.0, 5.0]). Collectively, the results demonstrate that SB supplementation can improve HI cycling capacity irrespective of prior warm-up intensity, likely due to blood alkalosis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| 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) | 0.002 | 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".