MétaCan
Menu
Back to cohort
Record W4391747171 · doi:10.3390/buildings14020496

Full-Scale Implementation of an Automated Connecting Device for Modular Construction

2024· article· en· W4391747171 on OpenAlexafffund
Laurence Picard, Pierre Blanchet, André Bégin‐Drolet

Bibliographic record

VenueBuildings · 2024
Typearticle
Languageen
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsUniversité LavalNatural Sciences and Engineering Research Council of Canada
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsModular designCable glandSystems engineeringProcess (computing)Modular constructionScale (ratio)EngineeringComputer scienceField (mathematics)Embedded systemMechanical engineeringOperating system

Abstract

fetched live from OpenAlex

Modular construction is characterized by assembling volumetric units on site. Once assembled on site, the structural integrity of modular buildings highly relies on connections that provide essential performance against critical loading conditions. Connections significantly impact field assembly activities, and previous research has highlighted the importance of their functional performance. In this study, the researchers focus on implementing automated connecting devices in a full-scale experimental project. It presents the implementation of a self-locking inter-modular connector and an investigation of the benefits and limitations of its application in modular building systems. This study also investigates the use of connectors as attachment points for modular handling and lifting. It evaluates the pros and cons of combining a single device’s connecting and lifting functions. The implementation of an automated connecting device in the building design process is covered as well as the evaluation of its impacts on architectural, structural, and functional considerations. Finally, the potential of automated connecting devices to improve modular building systems’ overall performance and efficiency is assessed, and guidelines are identified to facilitate their adoption.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.661
Threshold uncertainty score0.333

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 head0.009
GPT teacher head0.281
Teacher spread0.272 · 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 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

Citations3
Published2024
Admission routes2
Has abstractyes

Explore more

Same venueBuildingsSame topicBIM and Construction IntegrationFrench-language works237,207