BURIED VALLEY EARTHQUAKE HAZARDS IN EASTERN CANADA: DETECTION, MAPPING AND MONITORING USING GEOPHYSICAL TECHNIQUES
Bibliographic record
Abstract
Earthquake hazard mapping in Eastern Canada has revealed thick soft soils in juxtaposition with firm bedrock causing a wide range of soil-rock responses to earthquake shaking. Recent work in the Ottawa-Montreal region has shown anomalously large amplification of small strain (M2.0 − M4.5) local earthquakes associated with thick soft-soil basins filled with post-glacial deposits of low shear wave velocity clays and silts. The surrounding rock has high shear wave velocities: hence soil-rock impedance contrasts are very large. Previous measurements of local earthquake shaking in these basins indicate amplifications and durations that cannot readily be explained by 1-D gradient amplification. It is suggested that basin-edge generated surface waves may be responsible for both constructive interference of wave trains within the basin, as well as prolonged duration of shaking. We have identified seven soft-soil basins in the Ottawa-Montreal corridor and have selected three contrasting ones for detailed examination. Accurate geotechnical basin frameworks have been developed and earthquakes are closely monitored with broad-band seismograph soil-rock pairs. Geophysical/geotechnical methods were applied to determine the shapes of the buried soil-rock boundary, the shear wave velocity-depth functions, the impedance contrasts, and the low-strain attenuation properties of the soil. Techniques include: surface shear wave refraction site measurements, landstreamer multi-component P and S reflection surveys, downhole seismic measurements, horizontal-to-vertical spectral ratios of ambient noise, and analyses of available borehole logs. Earthquake time-series analyses and 3-dimensional basin shake modeling are currently underway. Preliminary results indicate that, soft-soil basins do produce significant gradient and resonance amplification along with long duration “ring-on” surface waves compared to adjacent rock outcrop sites.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".