Insar Reveals Limited Summer Subsidence Two Decades After Wildfires Under the 2023 Heat Anomaly in North Yukon
Bibliographic record
Abstract
Permafrost stability is increasingly threatened by rising temperatures and extreme heat anomalies, particularly in wildfire-affected sub-arctic boreal regions. In this study, we applied InSAR to track permafrost ground deformation around several fire scars across Dempster Highway in North Yukon, Canada, focusing on its response to the recordbreaking 2023 heat anomaly. Our results show limited subsidence$(<10 \text{mm})$along the line-of-Sight (LOS) direction within the scars burned nearly and more than two decades ago, much smaller than that$(>20 \text{mm})$within unburned areas, while sustained frost heave up to 20 mm was detected in the previous freezing season. This can be interpreted as the permafrost aggradation due to the vegetation recovery and greening decades after the fire. These findings provide new insights into the resilience of boreal permafrost to climate extremes and highlight the importance of continuous InSAR monitoring to assess permafrost dynamics under increasing wildfire and warming trends.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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".