Ice Flow Speed Variability of the Vaughn Lewis Icefall, SE Alaska, From Tiltmeters
Bibliographic record
Abstract
Icefalls are steep ice flow features that form over steps in bedrock elevation. With their high driving stresses, icefalls have long been assumed to have a constant ice flowspeed. This assumption has not been thoroughly tested as methods using satellite feature tracking rapidly loose coherence and long-term GPS installations on the ground are unlikely to be retrievable. In this study, we test the hypothesis that the Vaughan Lewis Icefall in Southeast Alaska experiences daily velocity variations with daily variations in subglacial hydrology. Using high resolution tiltmeters, we observe change in ice surface tilt across eight days at two sites near the glacier centerline. We find daily variation in ice surface tilt, suggesting there are variations in daily ice flowspeed velocity. A weak and lagged correlation with air temperature suggests that velocity variations may be due to daily variations in subglacial hydrology. Future modeling efforts focused on describing ice flow over icefalls should consider adding daily or seasonal velocity variations. These results additionally have implications for theoretical models of ogive formation, which could result from seasonal flow speed variations across icefalls.
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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 | 0.000 |
| 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) | 0.001 | 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".