Spatial variability in periglacial terrain conditions, northwestern Canada
Bibliographic record
Abstract
Throughout much of northern Canada there is an inadequate knowledge of permafrost and periglacial terrain conditions, which impedes development of climate-resilient northern infrastructure, identification of potential geohazards, decision making regarding resource development, and inferring past and future landscape evolution. Using a land systems approach to better understand formation of landscapes and thaw-sensitive terrains of northern Yukon and northwestern Northwest Territories, we aim to describe the permafrost-related landform-sediment assemblages that exist in the region. Permafrost is continuous in the region, but variations in geology, landscape history, climate, relief, ecology, and other natural processes have produced a diverse range of permafrost conditions and landforms. Using the 875 km-long Dempster and Inuvik-to-Tuktoyaktuk highway corridors (DH-ITH) as a regional transect, and high-resolution satellite imagery, a robust methodology was implemented to identify and digitize (at 1:5000 scale) 8793 landforms (589 km2) within a 10 km-wide corridor (8530 km2) and classify them according to main formational process (hydrological, periglacial, and mass movement). Surficial geology data were extracted from available data sets. Landform densities in all feature classes vary substantially along the transect according to physiographic region and surficial geology. The northern 39% of the corridor is characterized by generally rolling or planar relief, numerous waterbodies (19%), and the remaining land area by mostly morainal (67%), glaciofluvial (12%), lacustrine (7%), and alluvial (7%) deposits. By count, it contains 53% of mapped features and the majority of periglacial (67%) and hydrological (70%) features. In particular, the Tuktoyaktuk Coastlands, Peel Plain, and Mackenzie Delta, contain the greatest density of mapped landforms within the corridor, which cover nearly 23%, 15%, and 15% of the land area of these physiographic regions, respectively. These extents reflect the amount of ground ice and level of permafrost-thaw sensitivity of these regions. In contrast, the physiographic regions of the southern 61% of the study area are characterized by high relative relief, few waterbodies (0.2%), and the land area mainly by colluvial (63%), alluvial (18%), and morainal (14%) deposits. Most mass movement features occur here (85% by count), and are concentrated in the Ogilvie Mountains (n = 1027; 108 km2). This feature inventory provides the basis for developing spatial models of landscape-thaw susceptibility, which can inform risk assessment and improve decision making regarding public safety and environmental management.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 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".