Integration of Building Information Modeling (BIM) and Virtual Design and Construction (VDC) with Stick-Built Construction to Implement Digital Construction: A Canadian General Contractor’s Perspective
Bibliographic record
Abstract
Building information modeling (BIM) and virtual design and construction (VDC) are useful management processes and methodologies to enhance project communication and coordination. Over the past few decades, researchers and practitioners have made efforts to promote the adoption of BIM and VDC in the construction industry. However, currently, the promotion and adoption of BIM and VDC are relatively slow in North America. This paper focuses on developing an approach to drive the adoption of the technologies through cooperation among project stakeholders and proposing a method of collaboration through a case study. In this paper, the authors surveyed and interviewed a major Canadian general contractor on its implementation of BIM and VDC in construction projects. The was to benchmark the status of BIM and VDC applications in the Atlantic region of Canada from a general contractor’s perspective. Both surveys and interviews were conducted with various project participants throughout the organization. Based on the results, a “Digital Construction Framework for the Future” is proposed to increase the adoption of BIM and VDC. This research can provide a general understanding of BIM and VDC adoption in this particular general contractor and areas of improvement in transitioning to a more digital working construction environment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".