Postexercise Heat Loss and Hemodynamic Responses during Head-down Tilt Are Similar between Genders
Bibliographic record
Abstract
PURPOSE: We evaluated the hypothesis that during recovery from dynamic exercise in the 15 degrees head-down tilt (HDT) position, the attenuation of the fall in mean arterial pressure (MAP), cutaneous vascular conductance (CVC), and sweat rate, and the augmentation of the rate of esophageal temperature (T(es)) decay relative to the upright seated (URS) posture, would be different between males and females. METHODS: Fourteen subjects (seven males, seven females) performed two experimental protocols: 1) 15 min of cycle ergometry at 75% VO2peak and then 60 min of recovery in the URS posture; or 2) 15 min of cycle ergometry at 75% VO2peak and then 60 min of recovery in the 15 degrees HDT position. Mean skin temperature, Tes, CVC, sweat rate, cardiac output (CO), stroke volume (SV), heart rate (HR), total peripheral resistance (TPR), and MAP were recorded at baseline; end of exercise; 2 min, 5 min, 8 min, 12 min, 15 min, and 20 min after exercise; and every 5 min until the end of recovery (60 min). RESULTS: During recovery from exercise, we observed significantly greater values for MAP, CVC, and sweat rate with HDT in comparison with the URS recovery posture (P <or= 0.05). The magnitude of these responses to HDT did not differ between genders, and a significantly lower T(es) was subsequently observed with HDT for the duration of recovery (P <or= 0.05) for both males and females. In the URS posture, females showed a greater decrease of postexercise MAP than did males (P <or= 0.05). At the end of 60 min of recovery, T(es) remained significantly elevated above baseline with the URS recovery posture (P
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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) | 0.000 | 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) | 0.003 | 0.001 |
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".