Effects of Hyperoxic Training on Performance and Cardiorespiratory Response to Exercise
Bibliographic record
Abstract
PURPOSE: To determine whether training in a hyperoxic environment would result in greater increases in VO2max and performance at 90% VO2max as compared with training in normoxia. METHODS: In a single blind design nine athletes trained for 6 wk on a cycle ergometer 3 d.wk(-1), 1 h.d(-1) (10 x 4-min intervals, with 2 min of rest between intervals) at 90% HR(max). Training HR range was maintained by adjusting the power output. Subjects were randomly assigned to H (60% O2) or N (21% O2) breathing conditions for training. After 12 wk of detraining, a second 6-wk training protocol was completed with the breathing conditions reversed. VO2max, performance time at 90% VO2max and cardiorespiratory response to a steady-state exercise at 80% VO2max were measured pre- and posttraining. All pre- and posttraining tests were conducted under normoxic conditions. RESULTS: There were no significant differences between pretraining results for any of the parameters. Power output was 8.1% higher while training in H compared with N, to maintain training HR. Both H and N training resulted in increased performance time, with H being greater than N. Although there was a trend for a greater increase in VO2max after H versus N training, this difference was not significant. HR(max) did not change for H or N. HR VE at 80% VO2max decreased posttraining with no differences between H and N. CONCLUSION: The data showed that a higher power output was required to maintain HR during H training. This increased training intensity during H resulted in improved exercise performance whereas cycling at 90% VO2max in room air and may be due to peripheral factors because cardiorespiratory responses were similar.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".