Implementation of a BIM Solution in a Small Construction Company
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.
Bibliographic record
Abstract
The challenges to produce with more quality, less cost and less leading time, drove the construction sector to find new process and tools to help them achieve these goals. Building Information Modeling (BIM) is a solution for these demands supported by many researchers and companies. Many enterprises had already started the BIM adoption process and many studies have been conducted. Unfortunately, the majority of studies are focused in big companies and developed countries, leaving medium and small companies, especially the ones in developing countries, without data to analyze the feasibility and advantages to enter this process and to guide them through it. In light of this, this paper provides a description of a BIM deployment process in a small construction company in Brazil. The case study presents an implementation process which includes seven steps, some of them still ongoing. Even with an unfinished BIM deployment process that was carried on without any known methodology, benefits derived from using BIM were observed and barriers for its full implementation were identified. Comparing these findings with the literature review, it may be noted that even if the size and country differs, most of the benefits and barriers are similar.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it