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Record W7135741652

Development of a geotechnical design standard for buildings in Canada

2022· report· en· W7135741652 on OpenAlexaffabout
Gordon A. Fenton, Pengpeng; id_orcid 0000-0001-7677-9370 He, Gennaro Esposito, Reza Rahimi

Bibliographic record

VenueDiscovery Research Portal (University of Dundee) · 2022
Typereport
Languageen
Field
Topic
Canadian institutionsDalhousie University
Fundersnot available
KeywordsGeotechnical investigationBridge (graph theory)Reliability (semiconductor)Resistance FactorsDesign methodsFoundation (evidence)
DOInot available

Abstract

fetched live from OpenAlex

Canadians are in the enviable position of having created a world-leading reliability-based geotechnical design code for bridges, namely Section 6 Foundations and Geotechnical Systems of CSA S6:19, Canadian highway bridge design code (CHBDC). Further research is now required to develop similar design provisions for the buildings, where a minimum geotechnical standard is currently lacking in Canada. It is anticipated that such design provisions would be beneficial and could be considered for a future standard.<br/><br/>This report summarizes the findings of a study that investigated target reliability levels for geotechnical systems and the resulting resistance factors required to achieve these reliability targets within a load and resistance factor design (LRFD) framework. The geotechnical problems considered include:<br/><br/>Seismic design of deep foundations;<br/>Seismic and wind loading design of shallow foundations;<br/>Sliding resistance of shallow foundations; and<br/>Sliding and overturning resistance of retaining walls.<br/>This report also summarizes the results of an investigation into direct reliability-based design as an alternative to the LRFD approach.<br/><br/>While most of the unknown resistance factors needed to develop a geotechnical design standard for buildings in Canada are calibrated in this report, areas that require additional research for the calibration of geotechnical resistance factors are identified in the summary.

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)0.010
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.133
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0020.002
Research integrity0.0000.002
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 head0.156
GPT teacher head0.351
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.

Study designNot applicable
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
Published2022
Admission routes2
Has abstractyes

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