Blind comparison of non-invasive shear wave velocity profiling with invasive methods at bridge sites in Windsor, Ontario
Bibliographic record
Abstract
Canadian seismic design guidelines classify subsurface ground conditions based on the average shear-wave velocity (VS) of the upper 30 m (VS30). We seek to optimize a robust earthquake site classification procedure for Ontario bridge sites, assessed primarily from blind comparison of non-invasive and invasive shear-wave velocity (VS) depth profiling techniques. Non-invasive seismic testing is performed at 6 bridge sites in Windsor, Ontario co-located with invasive penetration and/or borehole VS measurements. Non-invasive surface wave dispersion and site amplification functions are jointly inverted to retrieve VS profiles at each site. Bridge sites tested are found to be mostly characterized with sediments up to ~30 m thick overlying seismic bedrock. Excellent agreement of VS30 estimates is obtained between both invasive and non-invasive methods and we notably determine an overall average relative difference in VS between methodologies of 9% for soil layers. Earthquake site classification based on VS is consistent at all sites regardless of methodology.
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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".