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Record W2117819612 · doi:10.1139/cjce-2013-0498

Assessment of the structural reliability of loadbearing concrete masonry designed to the Canadian Standard S304.1

2014· article· en· W2117819612 on OpenAlexafffundvenueabout
Hadi Moosavi, Yasser Korany

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2014
Typearticle
Languageen
FieldDecision Sciences
TopicProbabilistic and Robust Engineering Design
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMasonryReliability (semiconductor)Structural engineeringStructural loadGeotechnical engineeringEngineeringIndex (typography)Forensic engineeringComputer science

Abstract

fetched live from OpenAlex

A structural reliability analysis was performed on concrete masonry under axial compression using the First Order Reliability Method (FORM) to assess the reliability levels under the current (2004) and preceding (1994) editions of the Canadian masonry design standard S304.1. The Hasofer–Lind reliability index was evaluated at different live-to-dead load and snow-to-dead load ratios using the Rackwitz–Fiessler procedure. The reliability analysis revealed that neither the masonry material resistance factor of 0.6 adopted in the current Canadian masonry design standard (S304.1-04) nor the previous value of 0.55 in its predecessor (S304.1-94) achieve acceptable reliability levels for masonry in compression under combined dead and live or snow loads. Reliability levels close to the target reliability index recommended by the Canadian standard S408-11 and the levels evaluated for concrete in compression designed to the Canadian standard A23.3-04 were achieved when a masonry material resistance factor of 0.5 was used.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.589
Threshold uncertainty score0.816

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.264
Teacher spread0.242 · 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 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

Citations11
Published2014
Admission routes4
Has abstractyes

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