Lithalsa Degradation and Thermokarst Distribution, Subarctic Canadian Shield
Bibliographic record
Abstract
In the North Slave region, permafrost developed in a time transgressive manner throughout the Holocene with lake-level recession, giving rise to the Great Slave Lowland and Great Slave Upland ecoregions of the subarctic Canadian Shield. Thermokarst in the region is commonly associated with degradation of numerous ice-cored mounds called lithalsas. Here we use site descriptions and air photos to document the distinctive geomorphic signatures associated with degrading lithalsas and develop a conceptual model for lithalsa degradation in this region, which builds upon an earlier model of lithalsa development. Physical degradation of lithalsas is dominated by two main processes: (i) subsidence indicated by the common occurrence of ponded water with partially submerged standing dead trees, and (ii) colluviation of thawed sediments toward the lithalsa margin that results in a rampart. According to these diagnostic criteria, satellite image analysis suggests that lithalsas were more widespread at higher elevations in the past, but the majority have degraded. This explains, in part, the reduction of lithalsa abundance with increasing elevation. The results suggest that lithalsas are vulnerable to thaw. Following from our observations and findings, we develop a conceptual model of lithalsa degradation. It suggests that soil hysteresis effects would likely prevent re-initiation of lithalsa formation if permafrost were to re-aggrade in the future.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| 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".