Cryostratigraphical studies of ground ice formation and distribution in a High Arctic polar desert landscape, Resolute Bay, Nunavut<sup>1</sup>
Bibliographic record
Abstract
Ground ice distribution and abundance have wide-ranging effects on periglacial environments and possible impacts on climate change scenarios. In contrast, very few studies measure ground ice in the High Arctic, especially in polar deserts and where coarse surficial material complicates coring operations. Ground ice volumes and cryostructures were determined for eight sites in a polar desert, near Resolute Bay, Nunavut, chosen for their hydrogeomorphic classification. Dry, unvegetated polar desert sites exhibited ice content close to soil porosity, with a <45 cm thick ice-enriched transition zone. In wetland sites, suspended cryostructures and ice dominated cryofacies (ice content at least 2× soil porosity values) were prevalent in the upper ∼2 m of permafrost. Average ground ice saturation at those locations exceeded porosity values by a factor between 1.8 and 20.1 and by up to two orders of magnitude at the ∼10 cm vertical scale. Sites with the highest ice contents were historically submerged wetlands with a history of sediment supply, sustained water availability, and syngenetic and quasi-syngenetic permafrost aggradation. Ice enrichment in those environments were mainly caused by the strong upward freezing potential beneath the thaw front, which, combined with abundant water supply, caused ice aggradation and frost heaving to form lithalsa plateaus. Most of the sites already expressed cryostratigraphic evidence of permafrost degradation. Permafrost degradation carries important ecological ramifications, as wetland locations are the most productive, life-supporting oases in the otherwise relatively barren landscape, carrying essential functions linked with hydrological processes and nutrient and contaminant cycling.
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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 | 0.001 | 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) | 0.001 | 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".