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Record W4391564779 · doi:10.36680/j.itcon.2024.002

Construction 4.0: A comparative analysis of research and practice

2024· article· en· W4391564779 on OpenAlex
Nathalie Perrier, Aristide Bled First, Mario Bourgault, Nolwenn Cousin, Christophe Danjou, Robert Pellerin, Thibaut Roland

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.

Bibliographic record

VenueJournal of Information Technology in Construction · 2024
Typearticle
Languageen
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsEngineeringEngineering ethics

Abstract

fetched live from OpenAlex

This paper presents an overview of the existing literature on Construction 4.0 technologies over the past decade and their most common applications in both research and practice, aimed at achieving three objectives. First, the search for the most relevant articles on Construction 4.0, published in the scientific literature, and small firms that are developing and delivering 4.0 technologies in the construction industry allows to identify the numerous applications associated with Construction 4.0. Second, the applications found in the scientific literature and those identified in practice are classified and compared based on a framework consisting of three distinct axes. Third, the classification framework highlights current research trends and potential areas for future research, which can be summarized as follows: (i) development of hybrid digital solutions; (ii) alignment with effective collection of more structured data, smart interactive web technologies, robotics, autonomous systems, and intelligent built assets; and (iii) strengthen the capacities of artificial intelligence and machine learning.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.396
Threshold uncertainty score0.567

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.004
Science and technology studies0.0000.001
Scholarly communication0.0000.002
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 head0.022
GPT teacher head0.330
Teacher spread0.308 · 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