An Empirical Model for Successful Collaborative Design Towards Sustainable Project Development
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
Building design is developed into complexities, especially because of the emergence needs on applying a concept of sustainability. Aesthetic and engineering systems are no longer as main consideration in a design production process. Collaboration is needed to facilitate the integration of multiple knowledge and participants in a design process. In the process, multiple experts are required for achieving the best design. This paper purposes to discover issues and solutions as the important factors of collaborative design. Literature study is applied to determine the factors which are physical, technical, and social factors. They are found as three main aspects to be considered in supporting successful collaborative design. It is also found that recently, research in this area is directing for developing social factors as main issue. Factor analysis is also used as methodology to identify and analyze the similarities and interdependencies between factors. Analysis of data which is gained from designers and experts in Indonesia discovers that the three factors are reduced into two factors. The model of successful collaborative design is developed based on two findings in this research, that is not only conceptually but also empirically.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 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