Evolution of muscle phenotype for extreme high altitude flight in the bar-headed goose
Bibliographic record
Abstract
Bar-headed geese migrate over the Himalayas at up to 9000 m elevation, but it is unclear how they sustain the high metabolic rates needed for flight in the severe hypoxia at these altitudes. To better understand the basis for this physiological feat, we compared the flight muscle phenotype of bar-headed geese with that of low altitude birds (barnacle geese, pink-footed geese, greylag geese and mallard ducks). Bar-headed goose muscle had a higher proportion of oxidative fibres. This increased muscle aerobic capacity, because the mitochondrial volume densities of each fibre type were similar between species. However, bar-headed geese had more capillaries per muscle fibre than expected from this increase in aerobic capacity, as well as higher capillary densities and more homogeneous capillary spacing. Their mitochondria were also redistributed towards the subsarcolemma (cell membrane) and adjacent to capillaries. These alterations should improve O(2) diffusion capacity from the blood and reduce intracellular O(2) diffusion distances, respectively. The unique differences in bar-headed geese were much greater than the minor variation between low altitude species and existed without prior exercise or hypoxia exposure, and the correlation of these traits to flight altitude was independent of phylogeny. In contrast, isolated mitochondria had similar respiratory capacities, O(2) kinetics and phosphorylation efficiencies across species. Bar-headed geese have therefore evolved for exercise in hypoxia by enhancing the O(2) supply to flight muscle.
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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".