Using available time series of Passive and Active Microwave to develop SMAP Freeze/Thaw algorithms adapted for the canadian subarctic
Bibliographic record
Abstract
Seasonal terrestrial Freeze/Thaw cycle in Northern Quebec Tundra (Nunavik) determined and evaluated with Passive and Active Microwave Observations. SMOS time series data were analyzed to examine seasonal variations of soil freezing, and to assess the impact of snow cover and land cover on freeze-thaw cycle. Further, the soil freezing maps derived from SMOS observations compared to microwave active images in the region near Umiujaq and Field survey data. The objective is to develop algorithms to follow the seasonal cycle of freezing and thawing of the soil in the Tundra and Boreal forest. Field data shows that freezing and thawing dates vary much spatially at the local scale in the Boreal Forest and the Tundra. Therefore, the field validation of the F/T state maps at the regional scale will be very important. Agreement Factor derived from comparison of SMOS FT maps with daily in-situ data shows low values which does not seems to be acceptable. New parameters such as lake and pond as well as vegetation type and height present on surface have to be introduced in the algorithm to obtain more realistic estimations.
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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 | 0.000 |
| 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 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".