Outcomes of the State-of-the-art Symposium: status, challenges and future directions of offsite construction
Bibliographic record
Abstract
Offsite construction is facing slow adoption despite the fact it can be a suitable solution for addressing historical problems faced by the construction industry, such as labor shortages, construction safety, time and costs overrun, and waste. The controlled factory environment creates room for innovation similar to the techniques used in the manufacturing industry. Yet, as always, the progress and adaptation of innovative ideas are challenging in the construction sector. A growing role for off-site construction requires further research and development. More collaborative efforts, industry meetings, and academic symposia are needed to bring together different disciplines and bridge the current information gap. This paper aims to present the outcomes of the äóěSymposium on the State-of-the-Art of Modular Constructionäóť held in Gainesville, Florida from May 4th to 5th, 2017 that aimed to bring together major stakeholders in modular construction. It includes an analysis of the lectures and the survey that was distributed to industry and academic experts during the symposium. Also, it investigates the state-of-the-art of modular construction and focuses on the strengths, weaknesses, opportunities, and threats that come with this building technique.
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 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 | 0.001 |
| 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 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".