Snow cover mapping capabilities using RADARSAT standard mode data
Bibliographic record
Abstract
A total of 21 RADARSAT SLC data from Heimdalen area, Norway (61/spl deg/N, 9/spl deg/E) during snowmelt in 1997 have been geocoded and recalibrated and analysed for temporal and incidence angle dependencies. The study area is 128 km/sup 2/ catchment area covering altitudes from 1053 to 1853 m, where most of the area is above the treeline. The difference between wet snow and bare ground was found to be 13 dB for Standard Beam Mode (S) S, while the difference in S2 data the day after was 6 dB. The increase contrast was explained by the difference in incidence angle. This increased contrast between wet snow and bare ground for higher incidence angle are supported by surface scattering model results. Backscattering from dry snow is 2-3 dB lower than for bare ground. Temporal backscattering behaviour correspond to snow temperature measurements and demonstrates the capability of detecting the snow melt onset.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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; 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".