Improved prediction of the vertical distribution of ground ice in Arctic-Antarctic permafrost sediments
Bibliographic record
Abstract
Abstract Global warming and permafrost degradation are impacting landscapes, ecosystems and the climate-carbon system. Current ground ice and geohazard maps rely on the frost susceptibility of surficial sediments, and substantial areas underestimate ice abundance. Here we use a soil environmental model to show the importance of considering unfrozen water content (dependent on sediment type, soil water chemistry, and temperature) when assessing the frost susceptibility of sediments. Our ensemble modeling of the vertical structure and evolution of ground ice for fine to coarse-grained sediments matches reasonably well with field measurements at sites from the low Arctic to the cold and hyper-arid Dry Valleys of Antarctica. Our modeling indicates a need to re-evaluate how frost-susceptible sediments are identified when mapping ice-rich permafrost landscapes and provides a framework for the development of quantitative estimates of the vertical distribution of ground ice in permafrost sediments at regional scale.
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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) | 0.002 | 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".