Landslide susceptibility maps of the Sea to Sky Corridor, British Columbia - a qualitative approach
Bibliographic record
Abstract
Historically, the Sea to Sky Corridor has witnessed 155 reported landslide events in the last 154 years. As part of the Public Safety Geoscience Program at the Geological Survey of Canada, a preliminary landslide susceptibility mapping activity was undertaken. The resulting maps are presented as work-in-progress. The method used was a qualitative parametric approach based on the available landslide inventory and baseline information (Journeay and Monger, 1998; Riopel et al., 2006; Blais-Stevens, 2007; 2008abc; Blais-Stevens and Septer, 2008; Couture and Riopel, 2008). We divided the landslide susceptibility thematic mapping activity into producing two separate maps based on the more frequent types of landslides in the area and the fact that the parameters causing these types of landslides are very different from one another. One landslide susceptibility map was created for rock falls/rock slides and the other, for debris flows. In each map, a series of information layers (Fig. 1) was compiled from available documentation and/or derived from DEMs (Riopel et al., 2006; Couture and Riopel, 2008). From this information, a parametric equation was defined where the information layers served as parameters with each parameter being given a weight. The units within each layer of information were also given a rating (See examples of rating in Tables 1 and 2). The resulting equation gave a Susceptibility Index (SI) ranging between 0-1 for each (25 m x 25 m) pixel. For the final products, SI units were divided into four colour-coded categories, from Low (green), Medium-Low (yellow), Medium-High (orange), and High (red).
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| 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".