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Record W3018138076 · doi:10.1080/15623599.2020.1756028

Construction workspace management: critical review and roadmap

2020· article· en· W3018138076 on OpenAlexaff
C. A. Igwe, Fuzhan Nasiri, Amin Hammad

Bibliographic record

VenueInternational Journal of Construction Management · 2020
Typearticle
Languageen
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsConcordia University
Fundersnot available
KeywordsWorkspaceInterdependenceComputer scienceTask (project management)Space (punctuation)Process managementWork (physics)Scheduling (production processes)Management scienceConstruction engineeringSystems engineeringOperations managementEngineeringArtificial intelligenceSociology

Abstract

fetched live from OpenAlex

Construction workspace management has been a big issue in research and practice in recent years due to the need to improve productivity and safety by reducing spatio-temporal clashes in the management of construction projects. The complexities and dynamic nature of construction sites make construction workspace management difficult due to the continually evolving nature of the workspace. The space planning problem in construction has two main elements that are interdependent but require different approaches: the space scheduling problem, focused on the planning of task execution spaces, and the site layout problem, focused on the location of temporary facilities of various kinds. However, despite the importance of construction workspace management, a comprehensive review of the subject matter is absent in the literature. The objectives of this study are (1) to identify prominent themes in published research; (2) to compare work published within each theme; and (3) to suggest future directions for construction equipment space planning.

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)0.019
metaresearch head score (Gemma)0.044
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.019
Threshold uncertainty score0.098

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.044
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0180.015
Science and technology studies0.0020.003
Scholarly communication0.0050.009
Open science0.0040.003
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0080.002

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 head0.011
GPT teacher head0.242
Teacher spread0.231 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations30
Published2020
Admission routes1
Has abstractyes

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