Two-dimensional Simulation of Aerosol?Cloud Profile
Bibliographic record
Abstract
Developments of algorithm and computer graphics simulation are important to distinguish between aerosols and clouds in remote sensing data and images. The distribution of aerosols and clouds are needed to be known in order to study their interactions with one another and identify both affecting factors towards Earth’s climate stability. The objective of this paper is to expand the current work done in building new algorithm and simulation method to differentiate aerosols and clouds in spaceborne lidar data and images using image processing and computer graphics software, PCI Geomatica 10.1 and SCION Image. The new algorithm and simulation that has developed showed good results and clarify the vertical distribution of aerosols and clouds in the atmosphere. Plot profiles of clouds on both days showed higher pixel values than aerosol which are 255 compared to 234.04 and 244.11 for aerosols. Aerosols have been found consistently to have higher mean at altitude 0?5 km and 15?20 km on both days.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".