Concurrent engineering in Brazilian construction companies: Maturity assessment
Bibliographic record
Abstract
The purpose of this paper is to identify the maturity level of concurrent engineering in Brazilian construction companies in the Great Vitoria region – Espirito Santo. This is a qualitative research study, which proposes a methodology based on semi-structured and structured interviews applied in Brazilian construction companies, using nine case studies in construction companies of Great Vitoria (Espirito Santo, Brazil). The results confirm the appropriate methodology and confirm that the companies that were analyzed have, in general, a good and managed maturity level. The research also shows that the quality search initiated in the 1990’s in Brazil is valid, since quality was concurrent engineering’s most developed element in construction firms. However, there is still a lack of stakeholders’ integration and understanding of what a multidisciplinary team is and how it should work, which suggests that companies need to work harder in training and coordinating their teams. As the results show, it is also noticeable that certain firms’ characteristics, such as size, time in the market, centralization of decisions, among others, interfere in the level of maturity of concurrent engineering.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".