Spatio-temporal variability of soil moisture in the Canadian boreal forest and influence of the organic soil layer
Bibliographic record
Abstract
The boreal forest is one of the world's largest biomes. It is undergoing rapid transformations due to anthropogenic modifications and climate change. Water availability is critically important for the prediction of wildfires and other climate-induced processes. Therefore, the monitoring of soil moisture (SM) within this region is of great importance. However, very few remote sensing validation studies have focused on this biome, including the Soil Moisture Active Passive (SMAP) mission. The presence of a thick organic soil layer above the mineral layer is a soil characteristic distinctive to this biome. The sensitivity of SM within each of these soil layers to the SMAP SM product is of great interest. To investigate this uncertainty, a network of SM monitoring stations was installed within a SMAP pixel in the boreal forest region of central Saskatchewan, Canada. These results have importance for understanding the spatio-temporal variability of SM in the Canadian boreal forest.
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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 | 0.001 | 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 | 0.001 | 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 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".