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Record W4403270709 · doi:10.1016/j.sftr.2024.100335

Impact of the metaverse on sustainability in the construction industry

2024· article· en· W4403270709 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueSustainable Futures · 2024
Typearticle
Languageen
FieldEngineering
TopicDigital Transformation in Industry
Canadian institutionsCégep de ChicoutimiUniversité du Québec à Chicoutimi
FundersFonds de Recherche du Québec-Société et CultureCanada Research Chairs
KeywordsSustainabilityMetaverseBusinessComputer scienceEcologyHuman–computer interaction

Abstract

fetched live from OpenAlex

This article explores the contribution of the metaverse for improving sustainability in construction. A systematic literature review identifies 24 publications for which a bibliometric analysis shows the most important authors, publications, keywords, institutions, and countries in the field. The content analysis reveals that the metaverse technology improves sustainable construction practices by fostering energy efficiency, optimizing material and human resources, reducing construction waste and the environmental impact of buildings, enhancing collaboration and communication between stakeholders, and concurring to sustainable construction. Yet, the metaverse remains confronted with technological, economic, social and cultural limitations ushering in a theory-based agenda for future research.

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.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.559
Threshold uncertainty score0.363

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 integrity0.0000.001
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 head0.006
GPT teacher head0.253
Teacher spread0.247 · 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