Vs30 Mapping of the Greater Montreal Region Using Multiple Data Sources
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Bibliographic record
Abstract
The metropolitan community of Montreal (MMC) is located in Eastern Canada and included in the western Quebec seismic zone characterized by shallow crustal earthquakes and moderate seismicity. Most of the urbanized areas are settled close to the Saint-Lawrence River and its tributaries and within the region, delimiting the extension of the clay deposits from the Champlain Sea. The influence of these recent and soft deposits on seismic waves has been observed after the 1988 M5.8 Saguenay earthquake and has proven to be crucial in seismic hazard analysis. The shear-wave velocity Vs averaged over the 30 m of soil, abbreviated Vs30, is one of the most used parameters to characterize the site condition and its influence on seismic waves. Since 2000, a site condition model has been developed for the municipalities of Montreal and Laval, combining seismic and borehole data for risk mitigation purposes. The paper presents an extended version of the Vs30 mapping for the entire region of the MMC, which accounts for half of the population of Quebec, including additional ambient noise recordings, recently updated borehole datasets, geological vector map and unpublished seismic refraction data to derive Vs profiles. The estimated Vs30 values for thousands of sites are then interpolated on a regular grid of 0.01 degrees using the inverse distance weighted interpolation approach. Regions with the lowest estimated Vs30 values where site amplification could be expected on seismic waves are in the Northeastern part and in the Southwest of the MMC. The map expresses in terms of site classes is compared with intensity values derived from citizen observations after recent felt. In general, the highest reported intensity values are found in regions with the lowest Vs30 values on the map. Areas where this rule does not apply, should be investigated further. This site condition model can be used in seismic hazard and risk analysis.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it