Assembly Solution for Modular Buildings: Development of an Automated Connecting Device for Light-Framed Structures
Bibliographic record
Abstract
The prefabricated construction industry, also known as off-site construction, has been operating in North America for several years now and differs from traditional construction in its much shorter project timelines, lower costs, and increased build quality. However, the lack of a suitable and efficient assembly solution has been identified by many as a barrier to the use of off-site construction for larger buildings. To maximise the benefits of off-site manufacturing for multistorey buildings, an automated connection solution is presented in this paper. A new plug-in self-locking device was developed according to the following product design phases: on-site observations, definition of the problem and product specifications, solution generation, prototyping, fabrication, and testing. The plug-in self-locking device allows the assembly process to be accelerated by eliminating the fastening steps and a higher completion of modules off-site to be achieved. The design bears the compressive, tensile, and shear loads and contributes to the load path of the building.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".