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Record W4416597399 · doi:10.1080/17499518.2025.2591757

Effects of complex surficial geology on seismic amplification in Quebec, Canada

2025· article· en· W4416597399 on OpenAlexafffundabout
A. S. M. Fahad Hossain, Mohammad Salsabili, Ali Saeidi, Miroslav Nastev, Juliana Ruiz Suescun

Bibliographic record

VenueGeorisk Assessment and Management of Risk for Engineered Systems and Geohazards · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsWestern UniversityHydro-QuébecGeological Survey of CanadaUniversité du Québec à Chicoutimi
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsEngineering geologyDeformation (meteorology)Sedimentary rockMetamorphic rock

Abstract

fetched live from OpenAlex

Local geological and geotechnical conditions strongly influence the intensity and frequency content of seismic ground shaking. Seismic codes often use an amplification factor (AF) to adjust the rock-level response spectrum based on subsurface parameters. However, using a single parameter such as Vs30 or broad site classes may overlook regional variability, introducing bias in hazard assessments. In this study, we conducted nonlinear ground response analysis on 52 soil profiles from the Saguenay region , using six eastern Canadian ground motions scaled to five NBCC 2020 hazard levels. We examined how shear-wave velocity, total soil thickness, and till layers affect nonlinear amplification. We also evaluated different site proxies – Vs30, average shear-wave velocity (Vsavg), soil thickness (Hsoil), and fundamental site period (T0) – in capturing amplification behavior. Our results show that shear-wave velocity, soil thickness, and till layers significantly influence site response. Nonlinear soil behavior reduces amplification at high shaking levels, especially in stiff and shallow profiles, and shifts predominant periods. While Vs30 effectively captures short-to-medium period responses, T0 better represents long-period amplification. A comparison reveals that NBCC 2020 often overestimates amplification and underscores the need for site-specific micro-zonation using optimal site proxies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.664
Threshold uncertainty score0.856

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.006
GPT teacher head0.230
Teacher spread0.223 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes3
Has abstractyes

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