Bibliographic record
Abstract
Abstract Mixed‐phase clouds are recognized as significant contributors to the modulation of precipitation and radiation transfer on both regional and global scales. This study is focused on the analysis of spatial inhomogeneity of mixed‐phase clouds based on an extended data set obtained from airborne in situ observations. The lengths of continuous segments of ice, liquid, and mixed‐phase clouds present a cascade of scales varying from 10 2 km down to a minimum scale of 100 m determined by the spatial resolution of measurements. It was found that the phase composition of mixed‐phase clouds is highly intermittent, and the frequency of occurrence of ice, liquid, and mixed‐phase regions increases with the decrease of their spatial scales. The distributions of spatial scales have well‐distinguished power‐law dependencies. The results obtained yield insight into the morphology of mixed‐phase clouds and have important implications for improvement in representing subgrid inhomogeneity of mixed‐phase clouds in weather and climate models.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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; both teacher heads agree on what is shown here.
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".