Quantitative Assessment of Cryolithozone Landslide Process Variability (Banks Island Case Study)
Bibliographic record
Abstract
Abstract— Landsliding is among the most massive and active exogenous processes. Such processes are now occurring more and more actively in permafrost zones due to climate change, and require close attention and careful study. Analysis of a territory highly prone to these processes, namely Banks Island, one of the largest islands in northern Canada, confirms earlier studies of landslide processes in this zone, which indicate a relationship between increased activation of landslides and abnormally warm summers. The study and assessment of the landslide focus parameters in the southern part of Banks Island shows that in 1976–1999, the development of landslides was relatively uniform. Nevertheless, after 1999 there was a sharp increase in their size. We identify two types of landslide activation: broad activations in 1999, 2011, 2012, and 2013 with corresponding annual occurrence rates of 20–30 landslides; and occasional (local) activations, with landslides occurring at a rate of 1–2 annually in the intervals between the broad ones. The landslide foci have a random spatial distribution, though these processes take place in particular geological conditions and topography. The largest landslides reach 100 m along the slope and 50 m across the slope. With the help of cluster analysis according to the parameters of the sum of the length and width of landslides, six classes are distinguished, which differ primarily in the intensity and scale of movements. The spatial distribution of landslides by class of behavior in time is even more random than the distribution by year. No new activations after 2015 were identified within the research area. Undoubtedly, the study of the landslide frequency should be continued 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| 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".