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 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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".