Comparison of the relationships between lidar integrated backscattered light and accumulated depolarization ratios for linear and circular polarization for water droplets, fog oil, and dust
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Bibliographic record
Abstract
Recently, an empirical relationship between the layer integrated backscattered light and the layer accumulated depolarization ratio has been established for linear polarization for the case of water droplet clouds. This is a powerful relation, allowing calibration of space lidar and correction of the lidar signal for multiple scattering effects. The relationship is strongly based on Monte Carlo simulations with some experimental evidence. We support the empirical relationship with strong experimental data and then show experimentally and via second order scattering theoretical calculations that a modified relationship can be obtained for circular polarization. Also, we demonstrate that other empirical relationships exist between the layer accumulated linear and circular depolarization ratios and the layer integrated backscattered light for submicrometer particles and nonspherical particles.
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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 | 0.000 |
| 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