An Estimate of Ice Wedge Volume for a High Arctic Polar Desert Environment, Fosheim Peninsula, Ellesmere Island
Bibliographic record
Abstract
Abstract. Quantifying ground ice volume on a regional scale is necessary to assess the vulnerability of permafrost landscapes to thaw induced disturbance like terrain subsidence and to quantify potential carbon release. Ice wedges (IWs) are a ubiquitous ground ice landform in the Arctic. Their high spatial variability makes generalizing their potential role in landscape change problematic. IWs form polygonal networks visible on satellite imagery from active layer surface troughs. This study focuses on the estimation of IW ice volume for the Fosheim Peninsula, Ellesmere Island, a continuous permafrost area characterized by polar desert conditions and extensive ground ice. We perform basic GIS analyses on high resolution satellite imagery to delineate IW troughs and estimate the associated IW ice volume using a 3D subsurface model. We demonstrate two semi-automated IW trough delineation methods with different strengths to increase time-efficiency of this process, done manually in previous studies. Our methods yield acceptable IW ice volume estimates validating the value of GIS to estimate IW volume on much larger scales. We estimate that IWs are potentially present on 50 % of the Fosheim Peninsula (± 3000 km2) where 3.81 % of the top 5.9 m of permafrost could be IW ice.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".