Rapid Changes in Retrogressive Thaw Slump Dynamics in the Russian High Arctic Based on Very High‐Resolution Remote Sensing
Bibliographic record
Abstract
Abstract We used very high‐resolution satellite images to map the development of retrogressive thaw slumps (RTS) at six sites in the Russian High Arctic for the period 2011 to 2020. The 3,466 mapped RTS revealed an overall high activity, with site‐specific increases of RTS‐affected area up to +2,700% and RTS numbers up to +1,294%. For coastal sites, the changes in RTS‐affected area were mutually influenced by thermal abrasion at the bluff base and thermal denudation at the headwall. Overall, we observed strong erosion with average annual headwall retreat rates reaching up to −6.3 m/yr and bluff base retreat rates up to −5.2 m/yr. Similar to prior studies from the Canadian High Arctic, our findings suggest a rapid degradation response of ice‐rich permafrost in the rapidly warming Russian High Arctic.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 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 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".