Geo-referenced landslide information system for characterization of landslide hazards at the reservoir scale, Bridge River watershed, southwestern, B.C.
Bibliographic record
Abstract
Potential instabilities of reservoir slopes could endanger hydroelectric infrastructures, communication lines or communities. Reservoir slope inspections and on-going engineering geological assessments are the main components of dam safety programs. Even though institutions such as B.C. Hydro have been conducting slope-specific monitoring and assessments over long periods of time, there is a need to improve the current state of practice for landslide hazards on reservoir slopes. This thesis details the development of a preliminary standardized landslide information system, which consolidates essential spatial and non-spatial data necessary for reservoir slope assessments. The thesis outlines the design of the geodatabase and incorporation of landslide attributes, allowing standardization of landslide information. As a pilot project, the database is specific to the Bridge River area, in southwestern British Columbia. The database structure is sufficiently general, to allow its use in other regions as well. However, it is important to refine or optimize the design by potential users in order to meet their specific needs. One of the major results of the landslide geodatabase is the compilation of a landslide inventory of defined and potential landslides for the study area, which contains additional non-spatial data useful for reservoir slope inspections and assessments. In turn, the creation of a landslide geodatabase facilitates the characterization of landslide hazards at the reservoir scale by assessing specific available data, including the landslide inventory, terrain, bedrock and surficial geological and structural mapping. This provides a homogeneous and region-specific compilation of data relevant to landslide hazard assessment at the reservoir scale for bedrock and overburden-controlled slopes. Furthermore, this allows the study area to be divided into hazard sectors with approximately uniform characteristics. The results of this work should make landslide hazard information readily available at first hand to technically qualified users.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".