Mapping Arctic Bottomfast Sea Ice Using SAR Interferometry
Bibliographic record
Abstract
Bottomfast sea ice is an integral part of many near-coastal Arctic ecosystems with implications for subsea permafrost, coastal stability and morphology. Bottomfast sea ice is also of great relevance to over-ice travel by coastal communities, industrial ice roads, and marine habitats. There are currently large uncertainties around where and how much bottomfast ice is present in the Arctic due to the lack of effective approaches for detecting bottomfast sea ice on large spatial scales. Here, we suggest a robust method capable of detecting bottomfast sea ice using spaceborne synthetic aperture radar interferometry. This approach is used to discriminate between slowly deforming floating ice and completely stationary bottomfast ice based on the interferometric phase. We validate the approach over freshwater ice in the Mackenzie Delta, Canada, and over sea ice in the Colville Delta and Elson Lagoon, Alaska. For these areas, bottomfast ice, as interpreted from the interferometric phase, shows high correlation with local bathymetry and in-situ ice auger and ground penetrating radar measurements. The technique is further used to track the seasonal evolution of bottomfast ice in the Kasegaluk Lagoon, Alaska, by identifying freeze-up progression and areas of liquid water throughout winter.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".