Vs30 Derived from Geology: An Attempt in the Province of Quebec, Canada
Bibliographic record
Abstract
The influence of local site conditions is important when assessing the distribution of building damage and seismic risk. The average shear-wave velocity of the top 30 m of soil, Vs30, is one of the most commonly used parameters to characterize site conditions. Topographic slope is one of the proxies used to estimate Vs30 and is often used as a preliminary estimate of site conditions since a dataset is available worldwide at a resolution of 30 arc-seconds. This paper first proposes to compare the accuracy of Vs30 derived from topographic slope against detailed Vs30 zonation in five regions of the province of Quebec, Canada. A general underestimation of Vs30 is observed and site class agreement varies between 18 and 36% across the regions. Secondly, an approach is proposed to improve regional estimates of Vs30 where detailed site characteristics are not available other than the local topography and surface geology information. The surface deposit types from the geological map of Quebec are compared to Vs30 data previously obtained for zonation maps of Montreal, Saguenay and Gatineau in order to estimate Vs30 as a function of sediment deposit types as an alternative to the slope approach. A site class map for the province of Quebec is then proposed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".