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Record W4313340617 · doi:10.1139/cjce-2021-0543

Development of quick seismic evaluation procedure for existing buildings in Canada

2022· article· en· W4313340617 on OpenAlexaffvenueabout
Reza Fathi-Fazl, Farrokh Fazileh, Zhen Cai, W. Leonardo Cortés-Puentes

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2022
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsEvaluation methodsConstruction engineeringSeismic analysisKey (lock)Set (abstract data type)EngineeringComputer scienceCivil engineeringReliability engineering

Abstract

fetched live from OpenAlex

The National Research Council Canada (NRC) is currently developing seismic evaluation and upgrading guidelines for existing buildings in Canada. The seismic evaluation guidelines consist of three tiers of seismic evaluation procedures, that is, Tier 1 Quick Evaluation, Tier 2 Deficiency-Based Evaluation, and Tier 3 Detailed Evaluation. This paper presents the Tier 1 Quick Evaluation procedure, which aims to update the initial quick evaluation procedure in the existing seismic evaluation guidelines developed by the NRC in early 1990s. The proposed procedure covers seismic assessment of both structural and non-structural elements, and requires the review of construction documents, on-site inspection, and calculations. A set of checklists are contained to uncover potential key seismic deficiencies of the building under evaluation. The checklists are in the form of evaluation statements that relate to potential seismic deficiencies in the structural systems and non-structural components. The proposed procedure is demonstrated by conducting the seismic evaluation of an existing building that is part of a pilot study.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.015
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.535
Threshold uncertainty score0.924

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.031
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0090.004
Science and technology studies0.0030.001
Scholarly communication0.0020.002
Open science0.0020.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.003

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 head0.017
GPT teacher head0.213
Teacher spread0.196 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreMethods

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

Citations2
Published2022
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal of Civil EngineeringSame topicStructural Behavior of Reinforced ConcreteFrench-language works237,207