Separate and combined effects of dehydration and thirst sensation on exercise performance in the heat
Bibliographic record
Abstract
Using intravenous infusion, we separated the physiologic consequences of 3% body mass dehydration from the conscious awareness of fluid replacement on time trial (TT) performance in the heat. Eleven trained cyclists performed 90 min of steady-state (50% V ˙ O 2 peak ) cycling followed by a self-paced 20-km TT in a hot-dry (35 °C, 10% relative humidity, wind speed 3.0 m/s) environment while euhydrated-not thirsty (EU-NT), euhydrated-thirsty (EU-T), dehydrated-not thirsty (DH-NT), or dehydrated-thirsty (DH-T). Thirst was manipulated by providing (NT) or withholding (T) ad libitum 35 °C water oral rinse. Distinct hydration states existed, with 0.4 ± 0.5% dehydration following the 20-km TT (EU) compared with 3.2 ± 0.6% in DH (P < 0.001). Greater perceived thirst existed in T (7 ± 2 on a 1-9 scale) than NT (4 ± 2, P < 0.001) after the TT. No significant differences in power output existed during the TT between hydration (EU 202.9 ± 36.5 W vs DH 207.0 ± 35.9 W, P = 0.362) and thirst conditions (NT 203.3 ± 35.6 W vs T 206.6 ± 36.8 W, P = 0.548), nor were there differences in completion time (P = 0.832) or pacing profile (P = 0.690). Within the range of up to 3% body mass loss, neither the physiologic effects from lowered hydration status nor the perception of thirst, separately or combined, affected sustained submaximal exercise performance in the heat for a healthy and fit population.
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 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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".