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Record W7117673134 · doi:10.52152/heranca.v8i4/1129

Material Analysis, Restoration and Protection of Modern and Contemporary Architectural Relics

2025· article· W7117673134 on OpenAlexaff
Cui Naiyuan, Deprizon Syamsunur, Salihah Surol, Lisa Oksri Nelfia, Jing Lin Ng, Mohammed Hamza Momade

Bibliographic record

VenueHerança · 2025
Typearticle
Language
FieldEngineering
TopicMasonry and Concrete Structural Analysis
Canadian institutionsDurham College
Fundersnot available
KeywordsSustainabilityCultural heritageConservationEnvironmental restorationImplementationCompatibility (geochemistry)Emerging technologies

Abstract

fetched live from OpenAlex

This study explores the potential of Reinforcement Sleeve Concrete Grouting Connection (RSCGC) technology as an innovative solution for restoring modern architectural relics. With the degradation of materials such as concrete, steel, and prefabricated components in contemporary buildings, the study aims to evaluate how this advanced restoration method can enhance the structural integrity and longevity of modern buildings while preserving their historical and cultural value. This research utilizes the systematic review method, examining 21 peer-reviewed journal articles, case studies, and technical reports on restoration methods and prefabricated construction technology. The research aims to analyze the potential of RSCGC in enhancing material compatibility, structural reinforcement, and authenticity preservation. The case studies comprise theoretical implementations and actual instances, providing an overall insight into the effectiveness of the technology across various settings. An analytical framework was employed to group restoration techniques by their compatibility with contemporary materials and their capacity for increasing the longevity of contemporary building structures. The findings suggest that RSCGC offers significant advantages over traditional restoration methods, including improved structural durability, faster application times, and compatibility with modern construction materials. It also offers enhanced sustainability by reducing material waste and minimizing long-term maintenance costs. However, the study also identifies the need for more diverse case studies and long-term empirical data to fully assess the technology’s effectiveness in various contexts. This study contributes to the growing body of knowledge on integrating advanced construction technologies into heritage conservation practices. It highlights the importance of modernizing restoration approaches to preserve modern architectural heritage, offering a potential paradigm shift in conservation strategies.

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)0.009
metaresearch head score (Gemma)0.013
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.003
Science and technology studies0.0010.003
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.001
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 head0.010
GPT teacher head0.212
Teacher spread0.202 · 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
Published2025
Admission routes1
Has abstractyes

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