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Record W4399178667 · doi:10.3389/fbuil.2024.1380106

Modeling and categorizing standardized artifacts for scheduling occupancy on building construction sites

2024· article· en· W4399178667 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

VenueFrontiers in Built Environment · 2024
Typearticle
Languageen
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsOccupancySchedulePlan (archaeology)Scheduling (production processes)Process (computing)ReuseConstruction managementSpace (punctuation)Computer scienceTransport engineeringOperations researchWork (physics)EngineeringConstruction engineeringSystems engineeringCivil engineeringOperations management

Abstract

fetched live from OpenAlex

The new trend in planning building projects involves incorporating space management on the construction site. Failing to consider the management of site operations can lead to either relaxed or congested construction sites. This is because labor, tools, equipment, and materials all require space. It is important to plan for the circulation and temporary storage of materials, including recycling, reuse, and disposal. Temporary installations and finished products also take up space and can impact traffic flow. For example, partitions can impair traffic flow, while finished flooring can restrict it. The occupation of spaces also changes as the work progresses, so it is important to monitor and accommodate these changes. Therefore, space management needs to be coordinated throughout the construction phase. Traditional planning methods do not consider the analysis of critical spaces or their evolution over time. As a result, they produce schedules that do not reflect the reality of the construction site. Dynamic space-time planning means modelling the operational flow in different sectors of the construction site to optimize the construction process. Efficient space occupation allows for more effective utilization of available resources. This paper aims to analyze the spatial requirements of various construction operations and develop standardized artifacts that integrate spatial information into the schedule. To achieve this objective, the methodology aims to: (i) Conduct site surveys to collect data and analyze construction operations and their spatial needs; (ii) Define the necessary parameters for determining the occupancy rate (OR); (iii) Develop the needed artifacts for representing the static models based on the survey results and the developed occupancy parameters to visually depict and compute various types of occupancy and operations; (iv) Conduct workshops with the professionals in the construction industry. The participants were asked to provide feedback on whether the artifacts effectively captured the various aspects of construction work, such as equipment, tools, materials, and safety protocols. The aim is to validate that the artifacts as reliable representations of real-life construction scenarios. The feedback and input provided by the professionals helped to ensure that the artifacts were accurate, informative, and valuable for training purposes in the construction industry.

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: none
Teacher disagreement score0.460
Threshold uncertainty score0.667

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 head0.012
GPT teacher head0.223
Teacher spread0.211 · 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