Postglacial canyon incision primes ice-cored hillslopes for thaw slumping in the western Canadian Arctic
Bibliographic record
Abstract
Abstract Thaw-induced permafrost landslides, or thaw slumps, exemplify the alarming potential of rapid Arctic climate change to couple with unstable geomorphic feedbacks and escalate landscape hazards, sediment and solute fluxes, and carbon emissions. An emergent hot spot of thaw slump activity in the western Canadian Arctic provides an opportunity to understand the geomorphic context that predisposes some regions to extreme thaw sensitivity. Previous research suggests that slump concentration in this region may result from postglacial incision of ice-cored moraine along the historical margin of the Laurentide Ice Sheet. We assess this hypothesis in the Aklavik Range of the Northwest Territories, where we mapped 217 thaw slumps and reconstructed more than 3 m/k.y. of bedrock canyon incision since the Last Glacial Maximum. We find that thaw slumps tend to form between fluvially incised bedrock and relict till hillslopes. More than 75% of thaw slumping occurs within 500 m of incised bedrock, and hillslope normalized steepness explains over 33% of slump size variability. We interpret intense regional thaw slumping as a climate-sensitive landscape response to postglacial base-level change propagating into ice-cored hillslopes. This finding implies that the end-member permafrost disturbances observed in the western Canadian Arctic may be limited outside regions that share analogous geomorphic context.
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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 | 0.002 | 0.001 |
| 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".