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Record W7083445460 · doi:10.11159/ijci.2025.012

Reinforcement of Essential Structures with the Use of SLB Devices

2025· article· en· W7083445460 on OpenAlexvenueno aff

Bibliographic record

VenueInternational Journal of Civil Infrastructure · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Technological Innovation
Canadian institutionsnot available
Fundersnot available
KeywordsReinforcementNoise (video)Control (management)Action (physics)Control system

Abstract

fetched live from OpenAlex

The objective of this article is to study the control of the dynamic response of essential structures using SLB device.This type of dissipators has a high initial rigidity that allows it to operate from minimum values of displacement of the structure in the event of an earthquake.The theoretical and practical aspects related to the correct use of these dissipators are explained in detail.The ideal seismic resistance of a structure is that it presents displacements of a rigid system and forces of a flexible system.A rigid -flexible -ductile system presents intermediate responses between a flexible system and a rigid system.The maximum use of this concept in a structure lies in optimizing the use of dissipators and conventional walls to adequately control drifts and at the same time shear forces do not increase considerably in a flexible system.The Anglo-American Clinic was chosen as the existing structure to verify the efficiency of the dissipators.The structure initially presented torsional irregularity and the maximum drifts in both directions exceeded the established limit.With the addition of SLB dissipators on strategically placed decoupled walls, the torsional irregularity was corrected and the maximum drifts were reduced.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.441
Threshold uncertainty score0.431

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.022
GPT teacher head0.237
Teacher spread0.215 · 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 designTheoretical or conceptual
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
Published2025
Admission routes1
Has abstractyes

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