A decadal investigation of supraglacial lakes in West Greenland using a fully automatic detection and tracking algorithm
Why this work is in the frame
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Bibliographic record
Abstract
The sudden drainage of supraglacial lakes has been previously observed to initiate surface-to-bed hydrologic connections, which are capable of enhancing basal sliding, in regions of the Greenland Ice Sheet where ice thickness approaches 1 km. In this study, we develop a robust algorithm, which automatically detects and tracks individual supraglacial lakes using visible satellite imagery, to document the evolution of a population of West Greenland supraglacial lakes over ten consecutive melt seasons. Validation tests indicate that the algorithm is highly accurate: 99.0% of supraglacial lakes can be detected and tracked and 96.3% of reported lakes are true supraglacial lakes with accurate lake properties, such as lake area, and timing of formation and drainage. Investigation of the interannual evolution of supraglacial lakes in the context of annual melt intensity reveals that during more intense melt years, supraglacial lakes drain more frequently and earlier in the melt season. Additionally, the lake population extends to higher elevations during more intense melt years, exposing an increased inland area of the ice sheet to sudden lake drainage events. These observations suggest that increased surface meltwater production due to climate change will enhance the spatial extent and temporal frequency of lake drainage events. It is unclear whether this will ultimately increase or decrease the basal sliding sensitivity of interior regions of the Greenland Ice Sheet.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it