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Record W2889342920 · doi:10.11159/ijci.2018.004

Structural Design Developed in a BIM Environment: Benefits and Limitations

2018· article· en· W2889342920 on OpenAlexvenueno aff
Alcı́nia Zita Sampaio, Vitalino Azevedo

Bibliographic record

VenueInternational Journal of Civil Infrastructure · 2018
Typearticle
Languageen
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceSystems engineeringConstruction engineeringEngineering

Abstract

fetched live from OpenAlex

In the development of a building design it is important to produce accurate and reliable information, based on a high level of interoperability between systems. It is also necessary to establish good communication between those responsible committed in the project. The main objective of the study consists of a comparative analysis between the traditional process and the Building Information Modelling (BIM) methodology, focusing on the structural component of the project. The study allows the identification of limitations and problems resulting from the analysis of a specific case, and the proposed recommendations and best practices to promote achieving a higher degree of efficiency. Despite interoperability problems verified, the adoption of BIM methodology brings benefits to the Architecture, Engineering and Construction (AEC) sector through technical improvements, reducing the duration of tasks and increasing their efficiency.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.764
Threshold uncertainty score0.423

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 head0.021
GPT teacher head0.222
Teacher spread0.201 · 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 designObservational
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

Citations3
Published2018
Admission routes1
Has abstractyes

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