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Record W7005775966

Seismic landslide hazard mapping for Greater Vancouver, British Columbia

2019· article· en· W7005775966 on OpenAlexaboutno aff

Bibliographic record

VenueScholarship@Western (Western University) · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Micronutrient Interactions and Effects
Canadian institutionsnot available
Fundersnot available
KeywordsLandslideHazardNatural hazardHazard mapSeismic hazardSeismic microzonationPeak ground accelerationEpicenterStrong ground motion
DOInot available

Abstract

fetched live from OpenAlex

The lower Mainland of southwest British Columbia (BC) hosts about 3.5 million people and significant infrastructures of national importance. Southwestern BC has the highest seismic risk in Canada with significant potential to cause earthquake-induced hazards including tsunamis, liquefaction and landslides. A Cascadia mega-thrust (MW 9) earthquake is predicted to generate $75 billion Canadian dollars in losses. This damage can be resulted from ground shaking or its secondary phenomena like landslides; ground shaking during earthquakes may trigger landslides that can damage or destroy buildings, bury roads and highways and kill and injure people. In Canada, during the past century and a half, landslides have caused more fatality than all other natural hazards combined.\nSeismic hazard mapping for landslides integrates topographic, geotechnical and seismological information to develop the earthquake-induced slope displacements map which is indicator of seismic landslide potential. In this study we use a pseudo-probabilistic Newmark displacement analyses for regional landslide susceptibility mapping and its application will be illustrated with developing earthquake induced landslide hazard map for the quadrangle in Greater Vancouver area. The predicted displacements are assigned to the defined grids to come up with the final seismic landslide hazard map. The seismic landslide hazard map predicts very low hazard level (displacementcm) for the selected region which is in agreement with the observations in our field survey in July 2018 where no signs of deformation were recorded (e.g. cracks, settlements, previous landslides, scarps).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.160
Threshold uncertainty score0.878

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.050
GPT teacher head0.244
Teacher spread0.194 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

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