Reconstructing Glacier Surge Kinematics Using a Numerical Ice‐Flow Model Applied to the Dusty Glacier, St. Elias Mountains, Canada
Bibliographic record
Abstract
Abstract Long‐term records of the flow patterns and dynamics of surge‐type glaciers improve our understanding of their underlying dynamic processes, and are critical to better resolve their contribution to a changing cryosphere. We adapt a modeling approach designed to emulate glacier surging and fold kinematics using the full Stokes ice‐flow model Elmer/Ice to simulate surging of the Dusty Glacier, located in the St. Elias Mountains, Canada. We combine distributed mass‐balance and numerical ice‐flow models to reconstruct the fold kinematics of the 2001–2003 surge of the Dusty Glacier by comparing model results to Landsat‐7 and Sentinel‐2 imagery, and assess the sensitivity of centennial‐scale modeled glacier structure to different mass balance and sliding parameterizations. This study demonstrates the feasibility of using the approach to reconstruct the surface structure kinematics of a surge‐type glacier in nature, highlighting its potential application to other surge‐type glaciers and regions.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".