Robust Earthquake Site Classification Assessment at Ontario Bridge Sites.
Bibliographic record
Abstract
Canadian seismic design guidelines classify subsurface ground conditions based on the average shear-wave velocity (VS) of the upper 30 meters (VS30). We seek to optimize a robust earthquake site classification procedure for Ontario bridge sites, assessed primarily from blind comparison of non-invasive VS depth profiling techniques. Non-invasive seismic testing is performed at 10 bridge sites in southern 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. A general correlation between corrected VS and cone tip resistance (qc1) is developed for all soils encountered in Windsor, Ontario. We determine an overall average relative difference in VS between methodologies of 17% for soil layers at all bridge sites. Earthquake site classification based on VS is consistent at all sites regardless of methodology. Non-invasive techniques offer an efficient but lower-resolution VS profiling alternative to invasive earthquake site classification techniques with the advantages of measuring site period and VS of the impenetrable substratum.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 | 0.001 |
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".