ETUDE DE LA VARIABILITÉ CLIMATIQUE DES HAUTES LATITUDES NORD, DÉRIVÉE D'OBSERVATIONS SATELLITES MICRO-ONDES.
Bibliographic record
Abstract
Observing sub-polar ecosystems is important as they are suspected to change significantly in response to the expected increase in temperature for the next decades. To bypass the lack of meteorological stations in the Northern High Latitudes, remote sensing is an interesting alternative tool, covering almost the entire area. This project deals with the development of a method to derive surface parameters (>50ÀN) from satellite data. For this study, brightness temperature data acquired by the SSM/I (Special Sensor Microwave Imager) in the microwave spectrum are used because they are independent of solar radiation and weakly influenced by the atmosphere. Methods used are based on brightness temperatures measured at 19 and 37 GHz, which allow to derive three geophysical parameters related to climate variability: daily maps of snowcover between 1988 and 2002; a water surface extent (open water, small lakes, reservoirs, wetlands associated with low vegetation); a temperature characterizing the surface and the air above the ground. A method to normalize the temperature is presented to overcome the variation of the time of measurement. It leads to hourly series of temperature, This allows to study climate indicators such as the annual sum of positive degree days. Trends confirm observed climate evolution: increase of surface temperature (+0.8 +/- 0.4ÀC for Canada/Alaska between 1992 and 2002), decrease in snow extent cover. These original databases could also be useful for validation of regional climate model"--résumé abrégé par UMI.
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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 | 0.010 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".