3rd International Workshop on Landslides in Sensitive Clays: <i>From landslide mechanisms to social and environmental impacts</i>
Bibliographic record
Abstract
Sensitive1 clays deposits cover regions of the northern hemisphere where freshwater or seawater submerged lowlands during the last deglaciation. The silty to clayey sediments deposited in these sedimentary basins have been vertically uplifted by the subsequent emergence of the ground due to post-glacial isostatic rebound over the last few millennia. This process created landslide-prone slopes along rivers that incised these deposits. Over the same period, humans settled on these deposits, attracted by their proximity to rivers and the sea, as well as by the fertile soils, which fulfilled their needs for water, transport and agriculture. In North America, sensitive clays are mainly found in the lowlands of the Canadian provinces of Quebec, Ontario, Newfoundland and Labrador, and British Columbia, as well as in the U.S. states of Maine, Vermont and Alaska. In Europe, sensitive clays are mainly found in lowland regions of Norway, Sweden, Finland and Russia. Sensitive clay slopes can be affected by different types of landslides. Some events, such as superficial or single-rotational landslides, show little or no retrogression2, involve relatively small volumes, and occur with a frequency of several hundred events per year in Quebec. In contrast, more severe and destructive landslide, such as flowslides, spreads or flakes (Leroueil et al. this volume), shows large retrogression distance and large volume, but they are much less frequent. List of Bibliography is available in this PDF.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.045 | 0.012 |
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".