Combined analysis of SAR C and TM/Landsat data in the assessment of aquatic vegetation changes in the Tucurui reservoir, Para State, Brazilian Amazon
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Bibliographic record
Abstract
The objective of this study is to assess the changes in the aquatic vegetation in two different water levels of the Tucurui reservoir. During the SAREX 92 mission, for the first time, remote sensing data from the rising water stage became available for the entire reservoir. SAR-C data obtained over the entire reservoir in the wide mode were processed into a mosaic by the Canadian Centre for Remote Sensing. This mosaic was used to map the areas occupied by different stands of aquatic vegetation in April 1992. TM/Landsat color composite (band 3, 4 and 5) acquired in June 1992 was used to map the stands during the high water stage. The results showed that differences between SAR and TM data prevented the accurate assessment of the changes in the area occupied by aquatic vegetation.
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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 | 0.001 | 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 | 0.000 | 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