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Record W7115710738 · doi:10.71846/18-wcee-1410

IMPROVING NON-STRUCTURAL SEISMIC RESTRAINT IN CANADA

2025· article· en· W7115710738 on OpenAlexaboutno aff

Bibliographic record

VenueWorld Conference of Earthquake Engineering · 2025
Typearticle
Languageen
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsPrioritizationBuilding codePresentation (obstetrics)Construction industryTerm (time)Code (set theory)Building designCompatibility (geochemistry)

Abstract

fetched live from OpenAlex

Seismic restraint of non-structural elements in Canada is shaped by a standard called CSA-S832 published by the Canadian Standards Association, but is not formally codified. In Canada the term Operational and Functional Component (OFC) is used to describe all the components in a building that facilitate its occupancy, but are not part of the primary structural systems. This can range from facades and MEP systems, to furnishings and public art. The National Building Code of Canada provides force level calculations, general prescriptive limits on the types of restraint strategies, but there is no explicit reference to industry driven guidelines or exemptions. This has resulted in confusion, and mixed results in an industry segment that relies heavily on design by deferred submission during construction. Which can often lose sight of the primary design and performance goals of the primary project team. We will observe the differences in code mandates in the USA. The US market relies heavily on industry driven standards, such as SMACNA, which reasonably mirror the governing code for determining forces, ASCE 7. However, what remains outstanding is the understanding of risk and prioritization of restraint needs, and restraint compatibility between building systems, particularly MEP. Maintaining adequate physical gapping between mechanical and electrical systems is not clearly the responsibility of anyone when using the deferred submission delivery model. This presentation introduces the risk assessment theory embedded in CSA-S832 and outlines how its quantitative methodology can be used by a client to assess risk, quantify upgrades, and guide longer term mitigation efforts to address deficiencies that would otherwise be left unchanged through administrative provisions of the permitting process (i.e. grandfathering). Additionally, we will discuss how a more formal implementation of its methodology could be used by a project team to prioritize, coordinate, and dictate adequate restraint detailing across building systems and trade boundaries to achieve greater resilience outcomes.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.274
Threshold uncertainty score0.805

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.007
GPT teacher head0.179
Teacher spread0.172 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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