Impact of sodium citrate ingestion during recovery after dehydrating exercise on rehydration and subsequent 40-km cycling time-trial performance in the heat
Bibliographic record
Abstract
The purpose of this study was to assess the impact of sodium citrate (CIT) ingestion (600 mg·kg−1) during recovery from dehydrating cycling exercise (DE) on subsequent 40-km cycling performance in a warm environment (32 °C). Twenty male nonheat-acclimated endurance athletes exercised in the heat until 4% body mass (BM) loss occurred. After 16 h recovery with consumption of water ad libitum and prescribed diet (evening meal 20 kcal·kg−1, breakfast 12 kcal·kg−1) supplemented in a double-blind, randomized, crossover manner with CIT or placebo (PLC), they performed 40-km time-trial (TT) on a cycle ergometer in a warm environment. During recovery greater increases in BM and plasma volume (PV) concomitant with greater water intake and retention occurred in the CIT trial compared with the PLC trial (p < 0.0001). During TT there was greater water intake and smaller BM loss in the CIT trial than in the PLC trial (p < 0.05) with no between-trial differences (p > 0.05) in sweat loss, PV decrement, ratings of perceived exertion, or TT time (CIT 68.10 ± 3.28 min, PLC 68.11 ± 2.87 min). At the end of TT blood lactate concentration was higher (7.58 ± 2.44 mmol·L−1 vs 5.58 ± 1.32 mmol·L−1; p = 0.0002) and rectal temperature lower (39.54 ± 0.50 °C vs 39.65 ± 0.52 °C; p = 0.033) in the CIT trial than in the PLC trial. Compared with pre-DE time point, PV had decreased to a lower level in the PLC trial than in the CIT trial (p = 0.0001). In conclusion, CIT enhances rehydration after exercise-induced dehydration but has no impact on subsequent 40-km cycling TT performance in a warm uncompensable environment.
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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 | 0.001 |
| 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) | 0.001 | 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".