Flight response of slope‐soaring birds to seasonal variation in thermal generation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Summary Animals respond to a variety of environmental cues, including weather conditions, when migrating. Understanding the relationship between weather and migration behaviour is vital to assessing time‐ and energy limitations of soaring birds. Different soaring modes have different efficiencies, are dependent upon different types of subsidized lift and are weather dependent. We collected GPS locations from 47 known‐age golden eagles that moved along 83 migration tracks. We paired each location with weather to determine meteorological correlates of migration during spring and fall as birds crossed three distinct ecoregions in north‐east North America. Golden eagle migration was associated with weather conditions that promoted thermal development, regardless of season, ecoregion or age. Eagle migration showed age‐ and season‐specific responses to weather conditions that promoted orographic lift. In spring, adult eagles migrated earlier, over fewer days, and under more variable weather conditions than did pre‐adults, suggesting that adults were time limited and pre‐adults made choices to conserve energy. In fall, we found no difference in the time span of migration or when each age class migrates; however, we saw evidence that pre‐adults were less efficient migrants than adults. The decision by soaring birds to migrate when thermals developed allowed individuals to manage trade‐offs between migratory speed and migratory efficiency. When time was limited (i.e. spring movement of adults speeding towards nesting territories), use of whatever lift was available decreased the time span of migration. When migration was not time limited (e.g. spring movements by pre‐adults, all movements in fall), eagles avoided suboptimal flight conditions by pausing migration, thus increasing the time span of migration while reducing energetic costs.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.007 | 0.001 |
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 it