Brief communication: Classification of thawed/frozen topsoil state by spectral gradient methods based on SMAP and GCOM-W1 radiometric data
Bibliographic record
Abstract
Abstract. From 2015 to 2020, using spectral gradient radiometric methods, the possibility of frozen/thawed state identification of tundra soils was investigated based on SMAP and GCOM-W1 satellite observations of ten test sites located in the Arctic regions of Canada, Finland, Russia, and U.S.. It is shown that the spectral gradients of brightness temperature and reflectivity, measured on the frequency range from 1.4 GHz to 36.5 GHz on horizontal polarization with a determination coefficient from 0.775 to 0.834, root-mean-square-error from 6.6 days to 10.7 days, and bias from -3.4 days to +6.5 days, make it possible to identify the thawed/frozen state of the tundra soils. Spectral gradient methods have a significantly higher accuracy for identification of frozen and thawed state of tundra soils in relation to single-frequency methods based on the calculation of polarization index.
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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) | 0.003 | 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".