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Role of Simulation in Construction Engineering and Management

2010· article· en· W1977950491 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

VenueJournal of Construction Engineering and Management · 2010
Typearticle
Languageen
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsCanadian Natural Resources
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSoftware deploymentKey (lock)Computer scienceConstruction managementSystems engineeringConstruction industryManagement scienceEngineering managementConstruction engineeringEngineeringSoftware engineeringCivil engineeringComputer security

Abstract

fetched live from OpenAlex

Construction simulation is the science of developing and experimenting with computer-based representations of construction systems to understand their underlying behavior. This branch of operations research applications in construction management has experienced significant academic growth over the past two decades. In this paper, the author summarizes his views on this topic as per his Peurifoy address, given in October 2008. The paper provides an overview of advancements in construction simulation theory as reported in literature. It then summarizes the key factors that contribute to successful deployment of simulation in the construction industry, and the key attributes of problems that make them more amenable for simulation modeling as opposed to other tools. The paper then provides an overview of long-term simulation initiatives leading to the next generation of computer modeling systems for construction, where simulation plays an integral role in a futuristic vision of automated project planning and control.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.252
Threshold uncertainty score0.619

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.002
GPT teacher head0.173
Teacher spread0.171 · 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