Rapid area change in pitch-up manoeuvres of small perching birds
Bibliographic record
Abstract
Rapid pitch-up has been highlighted as a mechanism to generate large lift and drag during landing manoeuvres. However, pitching rates had not been measured previously in perching birds, and so the direct applicability of computations and experiments to observed behaviour was not known. We measure pitch rates in a small, wild bird (the black-capped chickadee; Poecile atricapillus), and show that these rates are within the parameter range used in experiments. Pitching rates were characterized by the shape change number, a metric comparing the rate of frontal area increase to acceleration. Black-capped chickadees increase the shape change number during perching in direct proportion to their total kinetic and potential energy at the start of the manoeuvre. The linear relationship between dissipated energy and shape change number is in accordance with a simple analytical model developed for two-dimensional pitching and decelerating airfoils. Black-capped chickadees use a wing pitch-up manoeuvre during perching to dissipate energy quickly while maintaining lift and drag through rapid area change. It is suggested that similar pitch-and-decelerate manoeuvres could be used to aid in the controlled, precise landings of small manoeuvrable air vehicles.
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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 | 0.000 |
| 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".