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Record W4389893373 · doi:10.1139/cjce-2023-0126

Framework for the design of seismically isolated National Building Code of Canada Part 9 structures

2023· article· en· W4389893373 on OpenAlexaffvenueabout
Nolan Stratton, Hamed Amini Tehrani, Rajeev Ruparathna, Niel C. Van Engelen

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2023
Typearticle
Languageen
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsBase isolationFrame (networking)Seismic analysisEngineeringIsolation (microbiology)Building codeCode (set theory)Seismic isolationCivil engineeringConstruction engineeringForensic engineeringComputer scienceStructural engineering

Abstract

fetched live from OpenAlex

In Canada, most single-family wood-frame residential structures in seismically hazardous regions are constructed according to Part 9 of Division B of the National Building Code (or similar provincial standards) using nonengineering methods. These structures are expected to perform well during an earthquake regarding life safety but may sustain severe economic losses. Seismic isolation is an emerging technology that provides excellent life safety and economic performance. While this technology has proven effective at protecting structures from earthquakes, no nonengineering methodologies exist that are compatible with Part 9 methods. This limitation produces significant testing, design, and cost barriers that restrict the application of base isolation on vulnerable Part 9 structures. To eliminate or reduce these cost barriers, a program framework was developed to perform the engineering seismic design and analysis for a base-isolated Part 9 single-family residential structure. The proposed methodology further encourages the application of seismic isolation to Part 9 structures.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.618
Threshold uncertainty score0.760

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.002

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 head0.015
GPT teacher head0.210
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations0
Published2023
Admission routes3
Has abstractyes

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