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Record W2740950201 · doi:10.2495/sdp-v13-n1-24-35

Implementing a BIM collaborative workflow in the UK construction market

2018· article· en· W2740950201 on OpenAlexvenueno aff
Nidaa Alazmeh, Jason Underwood, Paul M. Coates

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2018
Typearticle
Languageen
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsnot available
Fundersnot available
KeywordsWorkflowBuilding information modelingBusinessConstruction engineeringProcess managementEngineeringComputer scienceOperations managementDatabase

Abstract

fetched live from OpenAlex

BIM Level 2, as defined by the UK government, sets out processes and standards that formalise and regulate the collaborative methods for producing, sharing and exchanging information during different stages of any construction project. For overseas organisations that are looking to invest in the UK construction market, they will most certainly need to consider developing their understanding and ability related to BIM in order to enable developing their capability and competency to compete. This paper presents a case study that focuses on the implementation of collaborative based BIM workflow at a large Chinese engineering and construction organisation, which has recently established operations in the UK. The BIM implementation has been achieved under a Knowledge Exchange Partnership framework between the organisation and an academic institution in the UK. The main aim for this partnership project was to transform the organisation’s traditional workflow to achieve a BIM based collaborative workflow, and to comply with BIM Level 2 requirements. The case study has been achieved by adopting an action research methodology, whereby the project affiliate was an active part of the implementation project and was managing and coordinating the partnership project between the organisation and academic partner. Results to date from the project will be documented in this paper. This includes highlighting key challenges, adopted strategies and tactics to overcome the obstacles, pockets of improvements and potential areas for future development.

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 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)0.001
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.496
Threshold uncertainty score0.236

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.007
GPT teacher head0.237
Teacher spread0.230 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations17
Published2018
Admission routes1
Has abstractyes

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