Development and Comparison of 3D Seismic Geology and Shear-wave Velocity Models of Metro Vancouver
Bibliographic record
Abstract
This study presents a 3D regional modeling of seismic geology and shear wave velocity (Vs) in Metro Vancouver for seismic microzonation and hazard prediction. Leveraging an extensive geodatabase compiled from invasive and non-invasive in situ data, including lithological logs and seismic field data, we delineated four major geological units: Holocene post-glacial and Pleistocene inter/glacial sediments, and Tertiary sedimentary and Pre-Tertiary Coast Mountain plutonic rocks. Seismic geology model integrates the four primary geological formations, leveraging significant impedance-based surfaces derived from meticulously analyzed borehole stratigraphic logs and Vs depth profiles sourced from 2333 georecords, enhancing its depth and accuracy. Through a meticulous comparison with established interpreted geological cross-sections, we have reaffirmed the robustness and reliability of our seismic geology modeling approach. A numerical 3D “geotechnical layer” Vs model with 11 isovelocity surfaces was developed using 688 Vs depth profiles. Comparison with microtremor amplification spectra confirms our 3D models' reliable use in predicting site amplification. We find that the combination of local geology (thicknesses) and Vs information outperforms prediction in fundamental peak frequency compared to using only local geology combined with regional Vs information. Our study contributes to advancing understanding of seismic hazards in Metro Vancouver, highlighting the importance of incorporating localized seismic site conditions for precise regional seismic hazard assessments.
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 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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".