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Record W2323843643 · doi:10.1061/41020(339)50

Virtual Supervision in Construction Projects

2009· article· en· W2323843643 on OpenAlexaff
Lahiru P. Silva, Janaka Y. Ruwanpura, Kasun Hewage

Bibliographic record

VenueConstruction Research Congress 2009 · 2009
Typearticle
Languageen
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British ColumbiaUniversity of Calgary
Fundersnot available
KeywordsPopularityKey (lock)Computer scienceFocus (optics)Information flowConstruction industryConstruction managementEngineering managementProcess managementKnowledge managementEngineeringConstruction engineeringComputer security

Abstract

fetched live from OpenAlex

Better utilization of supervision time is a key factor to improve communication in construction projects. Popularity of the remotely accessed cameras in construction industry has increased drastically in the last few years. The concept proposed in this paper is an information management and a supervision time optimization system called "Virtual Supervision" model. This model enables the supervisors and other stakeholders of a project to monitor construction activities remotely and address the issues by using a surveillance camera system integrated with a few other technological tools. The focus of the "Virtual Supervision" model is to improve the efficiency, communication, and worker satisfaction. The system facilitates efficient information flow between the site office, site, head office, and other relevant stakeholders.

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)0.002
metaresearch head score (Gemma)0.003
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.031
GPT teacher head0.303
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 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
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

Citations10
Published2009
Admission routes1
Has abstractyes

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