Optical distortion correction for liquid droplet visualization using the ray tracing method: further considerations
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Bibliographic record
Abstract
The original work of Kang et al (2004 Meas. Sci. Technol. 15 1104–12) presents a scheme for correcting optical distortion caused by the curved surface of a droplet, and illustrates its application in PIV measurements of the velocity field inside evaporating liquid droplets. In this work we re-derive the correction algorithm and show that several terms in the original algorithm proposed by Kang et al are erroneous. This was not evident in the original work because the erroneous terms are negligible for droplets with approximately hemispherical shapes. However, for the more general situation of droplets that have shapes closer to that of a sphere, with heights much larger than their contact-line radii, these errors become quite significant. The corrected algorithm is presented and its application illustrated in comparison with that of Kang et al.
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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 | 0.003 | 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) | 0.000 | 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