How animals glide: from trajectory to morphology
Bibliographic record
Abstract
Animals that glide produce aerodynamic forces that enable transit through the air in both arboreal and aquatic environments. The relative ease of gliding compared with flapping flight has led to a large diversity of taxa that have evolved some degree of flight capability. Glide paths are curved, reflecting the changing forces on the animal as it progresses through its aerial trajectory. These changing forces can be under control of the glider, which uses specific aspects of anatomy to modulate lift, drag, and rotational moments on the body. However, gliders share no single anatomical or behavioral feature, and some species are unspecialized for gliding, producing aerodynamic forces using posture and orientation alone. Animals use gliding in a broad range of ecological roles, suggesting that multiple performance metrics are relevant for consideration, but we are only beginning to understand how gliders produce and control their flight from takeoff to landing. In this review, we focus on the physical aspects of how glide trajectories are produced, and additionally discuss the range of morphologies and postures that are used to control aerial movements across the broad diversity of animal gliders.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".