Effects of short‐term normobaric hypoxia on haematology, muscle phenotypes and physical performance in highly trained athletes
Bibliographic record
Abstract
This study aimed to determine the impact of short-term normobaric hypoxia on physiology and performance in highly trained athletes. Twelve (7 male and 5 female) athletes were randomly assigned into two groups and spent 8 h per night for two consecutive nights a week over 3 weeks under either short-term normobaric hypoxia (simulating 3636 m altitude, inspired O2=13%) or in normobaric normoxia in a single-blind study. Following a 3 week washout period, athletes were then exposed to the other condition. Athletes were tested for maximal oxygen consumption and time to exhaustion on an electromagnetically braked cycle ergometer before and after each treatment in addition to being tested for anaerobic performance (Wingate test) on a modified Monark cycle ergometer. Blood samples were taken throughout the experiment and vastus lateralis muscle biopsies were taken before and after each treatment. Increases in red blood cell count, haematocrit, haemoglobin, platelet number and erythropoietin concentration were observed following short-term normobaric hypoxia. Except for a modest decrease in phosphofructokinase activity following short-term normobaric hypoxia, no changes were observed in muscle enzyme activities, buffer capacity, capillary density or morphology. No performance measures were changed following short-term normobaric hypoxia or normobaric normoxia. Although short-term normobaric hypoxia exposure increased levels of a number of haematological parameters, this was not associated with improved aerobic or anaerobic performance in highly trained athletes.
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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".