Do high-altitude natives have enhanced exercise performance at altitude?
Bibliographic record
Abstract
Natives of high altitude (HA) may have enhanced physical work capacity in hypoxia due to growth and development at altitude or, in the case of indigenous Andean and Himalayan residents, due to population genetic factors that determine higher limits to exercise performance. There is a growing scientific literature in support of both hypotheses, although the specific developmental vs. genetic origins of putative population trait differences remain obscure. Considering whole-body measures of exercise performance, a review of the literature suggests that indigenous HA natives have higher mean maximal oxygen consumption (VO(2) (max)) in hypoxia and smaller VO(2) (max) decrement with increasing hypoxia. At present, there is insufficient information to conclude that HA natives have enhanced work economy or greater endurance capacity, although for the former a number of studies indicate that this may be the case for Tibetans. At the physiological level, supporting the hypothesis of enhanced pulmonary gas exchange efficiency, HA natives have smaller alveolar-arterial oxygen partial pressure difference ((A-a)DO(2)), lower pulmonary ventilation (VE), and likely higher arterial O(2) saturation (SaO(2)) during exercise. At the muscle level, a handful of studies show no differences in fiber-type distributions, capillarity, oxidative enzymes, or the muscle response to training. At the metabolic level, a few studies suggest differences in lactate production/removal and (or) lactate buffering capacity, but more work is needed in this area.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".