Automatic analysis and characterization of the hummingbird wings motion using dense optical flow features
Why this work is in the frame
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Bibliographic record
Abstract
A new method for automatic analysis and characterization of recorded hummingbird wing motion is proposed. The method starts by computing a multiscale dense optical flow field, which is used to segment the wings, i.e., pixels with larger velocities. Then, the kinematic and deformation of the wings were characterized as a temporal set of global and local measures: a global angular acceleration as a time function of each wing and a local acceleration profile that approximates the dynamics of the different wing segments. Additionally, the variance of the apparent velocity orientation estimates those wing foci with larger deformation. Finally a local measure of the orientation highlights those regions with maximal deformation. The approach was evaluated in a total of 91 flight cycles, captured using three different setups. The proposed measures follow the yaw turn hummingbird flight dynamics, with a strong correlation of all computed paths, reporting a standard deviation of [Formula: see text] and [Formula: see text] for the global angular acceleration and the global wing deformation respectively.
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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 | 0.001 |
| 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) | 0.000 | 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 it