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Record W2268329607 · doi:10.25916/sut.26262767

GFRP-steel hybrid reinforced concrete bridge deck slabs in Quebec, Canada

2013· article· en· W2268329607 on OpenAlexaboutno aff
Ehab A. Ahmed, Brahim Benmokrane

Bibliographic record

VenueSwinburne Research Bank (Swinburne University of Technology) · 2013
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsnot available
Fundersnot available
KeywordsFibre-reinforced plasticDeckBridge (graph theory)Bridge deckForensic engineeringStructural engineeringReinforced concreteEngineering

Abstract

fetched live from OpenAlex

In GFRP-Steel hybrid reinforced concrete (RC) bridge deck slabs, the non-corrodible glass fiber-reinforced polymer (GFRP) bars are used in the top reinforcement mat and the steel bars are used in the bottom reinforcement mat. This technique is being used by the Ministry of Transportation of Quebec (MTQ) in collaboration with the University of Sherbrooke (UdeS) as it is expected to yield cost-effective and durable concrete bridge decks. This paper highlights the recent hybrid-reinforced bridge deck applications on the extension of Hwy 410 in Sherbrooke (Quebec, Canada). So far, the project included four hybrid bridges where three of them were single-span simply supported bridges (P-15501, P-15502N, and P-15502S) and the fourth one was three-span continuously supported bridge (P-15604). In addition, this paper presents and discusses the typical results of the live load field tests conducted on the P-15502S bridge using three calibrated trucks.

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)0.000
metaresearch head score (Gemma)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.127

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.014
GPT teacher head0.224
Teacher spread0.210 · 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

Citations0
Published2013
Admission routes1
Has abstractyes

Explore more

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