The trans-Himalayan flights of bar-headed geese ( <i>Anser indicus</i> )
Bibliographic record
Abstract
Birds that fly over mountain barriers must be capable of meeting the increased energetic cost of climbing in low-density air, even though less oxygen may be available to support their metabolism. This challenge is magnified by the reduction in maximum sustained climbing rates in large birds. Bar-headed geese (Anser indicus) make one of the highest and most iconic transmountain migrations in the world. We show that those populations of geese that winter at sea level in India are capable of passing over the Himalayas in 1 d, typically climbing between 4,000 and 6,000 m in 7-8 h. Surprisingly, these birds do not rely on the assistance of upslope tailwinds that usually occur during the day and can support minimum climb rates of 0.8-2.2 km·h(-1), even in the relative stillness of the night. They appear to strategically avoid higher speed winds during the afternoon, thus maximizing safety and control during flight. It would seem, therefore, that bar-headed geese are capable of sustained climbing flight over the passes of the Himalaya under their own aerobic power.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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".