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Record W2069183482 · doi:10.1139/l08-041

Development of an index assignment procedure compatible with the regional seismicity in the province of Quebec for the rapid visual screening of existing buildings

2008· article· en· W2069183482 on OpenAlexafffundvenueabout
Amin Karbassi, Marie‐José Nollet

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2008
Typearticle
Languageen
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsÉcole de Technologie SupérieureUniversité du Québec à Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsInduced seismicityVulnerability (computing)Context (archaeology)Vulnerability assessmentIndex (typography)Vulnerability indexBuilding codeVisual inspectionCivil engineeringEngineeringComputer scienceStatisticsMathematicsGeology

Abstract

fetched live from OpenAlex

In the context of the seismic vulnerability evaluation of buildings, the score assignment method can be used as the first step of a multiphase procedure aimed at identifying hazardous buildings that must then be analysed in greater detail. Because the existing Canadian rapid visual screening procedure has not been updated since 1992, a new procedure is proposed based on a set of vulnerability indices for different cities in the province of Quebec. A seismicity level (low, moderate, or high) is attributed to each city using the spectral acceleration response values included in the 2005 edition of National building code of Canada (NBCC) and the criteria proposed in FEMA 310 Handbook for the seismic evaluation of buildings - a prestandard. The structural vulnerability indices (SVIs) are calculated using the recently improved nonlinear static analysis procedure in FEMA 440, Improvement of nonlinear static seismic analysis procedures for each seismicity level. The NBCC 2005 reference soil class C is considered in the calculation of the SVIs, and index modifiers for the building height, irregularities, and design and construction year. The application of these indices to the estimation of the probable damage distribution in building inventories is discussed at the end.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.139
Threshold uncertainty score0.966

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.022
GPT teacher head0.217
Teacher spread0.195 · 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 designSimulation or modeling
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

Citations28
Published2008
Admission routes4
Has abstractyes

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