Identification and characterization of alpine subglacial lakes using interferometric synthetic aperture radar (InSAR): Brady Glacier, Alaska, USA
Bibliographic record
Abstract
Abstract The temporary storage and subsequent release of water at glacial margins can cause severe flooding in downstream areas and substantially impact glacier dynamics. Alpine subglacial lakes may not be identified until they become subaerially exposed or release a jokulhlaup. We use interferometric synthetic aperture radar (InSAR) to identify and characterize three dynamic alpine subglacial lakes of Brady Glacier, Alaska, USA. We quantify changes in vertical displacement of the glacier surface and lake volumes from September 1995 through March 1996 using European Remote-sensing Satellite-1/-2 (ERS- 1/-2) tandem data. In the autumn, subsidence ranged from 4 to 26cmd-1 and the volume of water discharged ranged from 22 000 ± 2000 to 243 000 ± 14 000m3d-1. Subsidence and discharge rates declined significantly during the winter and continued at a lesser rate through March. Application of this technique may allow researchers to locate alpine subglacial lakes years or decades before they begin to release hazardous outburst floods and substantially impact glacier dynamics.
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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) | 0.000 | 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".