Assessment of the Topographic Wetness Index in Permafrost landscapes 
Bibliographic record
Abstract
Arctic permafrost regions are subject to rapid changes due to climate warming affecting hydrology, topography and ecology. Soil wetness is of great importance in these regions facilitating for example upscaling of carbon fluxes. In this study we therefore investigate the Topographic Wetness Index (TWI) as often used in land surface modelling, focusing on study regions in the Siberian and Canadian Arctic. We analyse the influence of the used Digital Elevation Model (DEM) by comparing results of the openly available ArcticDEM (2m resolution) and Copernicus DEM (30m resolution). Results are being validated against near-surface soil moisture in-situ measurements. Further comparisons are being made to other wetness indices such as the Tasselled Cap Wetness index or the Normalized Differential Moisture Index derived from Landsat 8. The relationship to InSAR derived surface displacements as an indicator of soil wetness is explored, as well as additional parameters such as the Topographic Position Index and correlations to other moisture indicators including land cover products.
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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 | 0.000 |
| 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 | 0.001 | 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".