Assessment of seismic hazards in British Columbia's north coast region (2013-2018)
Bibliographic record
Abstract
British Columbia's north coast (BCNC) has been the location of a number of development proposals over the last decade. As such, it has the potential to experience significant industrial, and consequently, economic and population growth. Negative impacts of geohazards, such as earthquakes and slope failures, and their secondary effects such as tsunamis could be detrimental to the region. Due to the historically low frequency of damaging geohazards in the BCNC, until 2013 there had been minimal research to understand them beyond the national-scale level. In 2013, Natural Resources Canada initiated a regional geohazard assessment, including marine and terrestrial-based research activities within BC's North Coast. The terrestrial-based component of the assessment specifically aimed to achieve a more detailed comprehension of active faulting, earthquake recurrence relationships, and strain accumulation patterns in the BCNC, necessary to improve seismic hazard models for use in the National Building Code of Canada. Through a multidisciplinary approach, including the deployment and monitoring of data from 7 new seismographs, it was confirmed that the regional seismicity pattern was, in general, being captured by the exisiting Canadian National Seismograph Network. However, the additional seismographs allowed for microseismicity patterns in the BCNC to be mapped in more detail. Displacements recorded on 8 new GNSS (Global Navigation Satellite System) stations show that the BCNC was, and is still (as of mid-2018) affected by the the 2012 MW 7.8 Haida Gwaii earthquake more than 150 km to the west. Over the course of this project a seismic microzonation study was conducted in the town of Kitimat, the town at the most inland extent of the Douglas Channel. Results of this study show that the geology underlying Kitimat is complex with a number of deep channels filled with soft, glaciomarine sediments, which are prone to amplification of up to approximately four times. Although this project was formally completed in March 2018, seismic, GNSS and InSAR monitoring will continue for a number of years to allow for a more detailed understanding of seismicity and crustal strain in the region. This, in turn, will allow for improved seismic hazard models with applications to building codes, engineering design, and decision-making.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".