Interpretation of Snow-Covered Ground ObjectsUsing RADARSAT Image
Bibliographic record
Abstract
In this paper, all 5 counties of Aletai, Buerjin, Jimunai, Habahe and Fuhai in Aletai region, Northern Xinjiang are selected as typical study area. By use of Canada RADARSAT data, the geometric correction and fundamental principles of radar remote sensing are studied. And the image interpretation is comparatively analyzed between the rectified geo-referenced radar image and images processed by brightness adjustment, edge enhancement, image enhancement, speckle suppressionand texture analysis methods. The interpretation indicators of radar image are established for the important objects closelyrelated to activities of relief snow disaster, such as cropland, river, traffic, residentialareas and etc. Results showed that microwave radar remote sensing can avoid the difficulties in monitoring of snow disaster using visible and near-infrared remote sensing data, which can provides scientific informationfor decision making in snow disaster areas.
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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 | 0.000 | 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) | 0.001 | 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 teacher head, 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".