Controls on permafrost-related landform distributions, Dempster and Inuvik-Tuktoyaktuk Highway corridors, northwestern Canada
Bibliographic record
Abstract
Knowledge of the distributions of permafrost landforms are important because they serve as indicators of ground ice conditions and thaw sensitivity.Permafrost degradation at these locations changes the physiographic, hydrologic, and ecologic conditions and impacts northern landscapes, wildlife, and infrastructure.Geospatial inventories of these landforms are time-consuming to make and are often limited in extent and landform type, reducing their utility to support informed decisions regarding land management, resource development, infrastructure design and maintenance, and climate adaptation strategies.Such inventories did not exist in northwestern Canada where permafrost degradation is modifying environmental system dynamics and challenging the performance of the Dempster and Inuvik-Tuktoyaktuk Highway (DH-ITH).We analyzed a new, comprehensive geodatabase of 8746 permafrost-related landforms (periglacial, mass movement, and hydrological features) developed for an 875 km-long, 10 km-wide DH-ITH corridor.Though intuitive, our findings demonstrate how broad-scale spatial distributions of 25 different permafrost-related landforms relate to surficial geology, glacial history, and permafrost conditions, which are intrinsic to the set of physiographic regions in this area.1
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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 | 0.002 |
| 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) | 0.003 | 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".