Exposure to a combination of heat and hyperoxia during cycling at submaximal intensity does not alter thermoregulatory responses
Bibliographic record
Abstract
In this study, we tested the hypothesis that breathing hyperoxic air (FinO2 = 0.40) while exercising in a hot environment exerts negative effects on the total tissue level of haemoglobin concentration (tHb); core (Tcore) and skin (Tskin) temperatures; muscle activity; heart rate; blood concentration of lactate; pH; partial pressure of oxygen (PaO2) and carbon dioxide; arterial oxygen saturation (SaO2); and perceptual responses. Ten well-trained male athletes cycled at submaximal intensity at 21°C or 33°C in randomized order: first for 20 min while breathing normal air (FinO2 = 0.21) and then 10 min with FinO2 = 0.40 (HOX). At both temperatures, SaO2 and PaO2, but not tHb, were increased by HOX. Tskin and perception of exertion and thermal discomfort were higher at 33°C than 21°C (p < 0.01), but independent of FinO2. Tcore and muscle activity were the same under all conditions (p > 0.07). Blood lactate and heart rate were higher at 33°C than 21°C. In conclusion, during 30 min of submaximal cycling at 21°C or 33°C, Tcore, Tskin and Tbody, tHb, muscle activity and ratings of perceived exertion and thermal discomfort were the same under normoxic and hyperoxic conditions. Accordingly, breathing hyperoxic air (FinO2 = 0.40) did not affect thermoregulation under these conditions.
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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) | 0.000 | 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) | 0.001 | 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".