Migration path annotation: cross-continental study of migration-flight response to environmental conditions
Bibliographic record
Abstract
Understanding the movements of animals is pivotal for understanding their ecology and predicting their survival in the face of rapid global changes to climate, land use, and habitats, thus facilitating more effective habitat management. Migration by flying animals is an extreme form of movement that may be especially influenced by weather. With satellite telemetry studies, and the growing availability of information about the Earth's weather and land surface conditions, many data are collected that can advance our understanding about the mechanisms that shape migrations. We present the track annotation approach for movement data analysis using information about weather from the North American Reanalysis data set, a publicly available, regional, high-resolution model-observation hybrid product, and about topography, from a publicly available high-resolution digital elevation model (DEM). As a case study, we present the analysis of the response to environmental conditions in three contrasting populations of Turkey Vultures (Cathartes aura) across North America, tracked with a three-dimensional GPS-based sensor. Two populations in the east and west coasts of the United States responded similarly to weather, indicating use of both slope and thermal soaring. Continental-interior, "Plains populations," exhibited a different migratory pattern primarily indicative of thermal soaring. These differences help us understand the constraints and behaviors of soaring migrants. The track annotation approach allowed large-scale comparative study of movement in an important migratory species, and will enable similar studies at local to global scales.
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How this classification was reachedexpand
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 | 0.000 | 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) | 0.011 | 0.002 |
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; both teacher heads agree on what is shown here.
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".