MétaCan
Menu
Back to cohort
Record W4414923614 · doi:10.1177/87552930251378247

Shake-table tests on two 40-ton reinforced concrete U-shaped walls with uniaxial and bidirectional-torsional response

2025· article· en· W4414923614 on OpenAlexaff
Ryan Hoult, António A. Correia, Alex Bertholet, Paulo Candeias, Gwendal Cumunel, C. Doneux, Denis Garnier, Yunhyeok Han, Tatjana Isaković, Antonio Janevski, Stefania Lo Feudo, Andrea Orgnoni, Basile Payen, Dan Palermo, Rui Pinho, Filipe Ribeiro, João Pacheco de Almeida

Bibliographic record

VenueEarthquake Spectra · 2025
Typearticle
Languageen
FieldEngineering
TopicStructural Load-Bearing Analysis
Canadian institutionsYork University
Fundersnot available
KeywordsFlexural strengthReinforced concreteResilience (materials science)Instrumentation (computer programming)Nonlinear systemFace (sociological concept)Experimental research

Abstract

fetched live from OpenAlex

Reinforced concrete (RC) structures, widely used in mid- to high-rise construction, face significant challenges related to sustainability, durability, and seismic resilience. Despite extensive experimental research on RC walls, studies specifically focusing on their torsional response remain limited. To address these gaps, the ERIES-ALL4wALL project investigates the torsional and bidirectional flexural behavior of RC U-shaped walls, a key structural feature in contemporary and future high-rise buildings. This article presents experimental findings from shake-table tests on two slender U-shaped walls, evaluating their nonlinear flexural and torsional performance under realistic seismic ground motions. Advanced instrumentation techniques—such as camera-based vibration measurements—are introduced to capture detailed performance data. The accompanying open-access data are then outlined, enabling further research and development of models to improve the resilience and sustainability of RC core walls in urban environments.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.568
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.005
GPT teacher head0.216
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 teacher head, not a consensus.

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

Citations4
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueEarthquake SpectraSame topicStructural Load-Bearing AnalysisFrench-language works237,207