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Record W4300686867 · doi:10.1139/cjce-2021-0432

Reliability-based calibration of the slenderness limit of concrete columns reinforced with GFRP bars for CSA S6 and CSA S806

2022· article· en· W4300686867 on OpenAlexafffundvenueabout
Koosha Khorramian, Fadi Oudah, Pedram Sadeghian

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2022
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of CanadaDalhousie University
KeywordsFibre-reinforced plasticReliability (semiconductor)Structural engineeringBucklingCalibrationLimit (mathematics)Reinforced concreteComputer scienceEngineeringMathematics

Abstract

fetched live from OpenAlex

The design provisions for internal glass fiber-reinforced polymer (GFRP) reinforced concrete (RC) columns have been recently under consideration by design committees in Canada and around the world due to new advancements in understanding the behavior of GFRP-RC columns. The slenderness limit is a critical design parameter differentiating between the first- and second-order analyses of GFRP-RC columns. The existing slenderness limits in design standards were calibrated using deterministic approaches. In this study, a novel reliability-based approach was utilized to quantify the reliability index associated with the slenderness limit to calibrate and propose optimized reliability-based slenderness limits for CSA S806 and CSA S6, for the first time. The method takes the advantage of artificial intelligence and incorporates a comprehensive experimental database.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.007
GPT teacher head0.170
Teacher spread0.163 · 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 designBench or experimental
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

Citations1
Published2022
Admission routes4
Has abstractyes

Explore more

Same venueCanadian Journal of Civil EngineeringSame topicStructural Behavior of Reinforced ConcreteFrench-language works237,207