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Record W780276202

Seismic performance-based design of bridges with quantitative local performance criteria

2010· article· en· W780276202 on OpenAlexfundaboutno aff
M. Neaz Sheikh, Frédéric Légeron

Bibliographic record

VenueResearch Online (University of Wollongong) · 2010
Typearticle
Languageen
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBridge (graph theory)Code (set theory)Relation (database)Seismic analysisComputer scienceEngineeringReliability engineeringCivil engineeringData mining
DOInot available

Abstract

fetched live from OpenAlex

Performance based design of bridges for earthquake resistance is still not explicitly used in design. However, most codes specify a level of performance for bridges under various earthquake inputs. In principle, design rules suggested in the code should meet stipulated performance criteria. However, it has been highlighted in the past that design rules are not directly related with stipulated performance criteria. After the presentation of performance criteria and their relation with post-earthquake functional requirements, the article examines the case of the Canadian Bridge Design Code (CAN/CSA-S6-06). Performance of bridges designed with this code is predicted and compared to expected levels. It is shown that compliance with design rule does not guarantee an adequate performance. This article attempts to correlate qualitative performance criteria with post-earthquake functional requirements, and critically examines code specified design rules and their cost effectiveness. Some implicit design rules are proposed to design new bridges.

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)0.001
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 score0.051
Threshold uncertainty score0.664

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.045
GPT teacher head0.285
Teacher spread0.241 · 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

Citations4
Published2010
Admission routes2
Has abstractyes

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