MétaCan
Menu
Back to cohort
Record W3018138076 · doi:10.1080/15623599.2020.1756028

Construction workspace management: critical review and roadmap

2020· article· en· W3018138076 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.

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.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.900
Threshold uncertainty score0.537

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 head0.011
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