Post‐Metabolic Response to Exercise in Normobaric Hypoxia
Bibliographic record
Abstract
The purpose of the study was to examine post‐metabolic response to constant workload exercise (CWE) under normobaric hypoxia. Seven active healthy males (age: 26±4 yrs; height: 176±4 cm; weight: 78±10 kg; BMI: 25±3 kg•m −2 ; VO 2max : 4.0±0.3 L•min −1 ) randomly underwent normoxic and hypoxic (F i O 2 = 0.15) CWE. Each experimental session consisted of a basal metabolic rate determination (BMR), 60‐min of CWE, and 60‐min of post‐exercise metabolic rate measurement. For each condition, 24‐hr post‐treatment BMR was recorded. Absolute workload was determined during a graded cycling test in normoxia and set at 50% of participants’ peak power (314±26 W) for both conditions. There was a significant condition/time (0–20; 21–40, and 41–60‐min) interaction on post‐exercise lipid metabolism ( p = 0.015). Fat contribution was 47±19%, 60±9% and 51±12% in normoxia; and 79±20%, 79±19% and 62±24% in hypoxia, for each epoch, respectively. Although not statistically significant, fat contribution 24‐hrs after the hypoxic intervention was elevated 3% above baseline. In conclusion, exercise in hypoxia contributed to an increase reliance on fat oxidation post‐treatment up to 24‐hrs. This result was explained by higher glycolytic flux during exercise under hypoxia compared to normoxia at the same absolute workload.
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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".