Mass Customisable Roofing Solutions for the New Build and Retrofit Markets in the UK
Bibliographic record
Abstract
Major house builders and contractors in the UK are seeking alternative solutions to form the structural frame of pitched roofs for various reasons; speed, health and safety, quality ease of use. They are exploring the use of offsite systems, which arguably provide all of the above benefits. However, these systems are typically considerably more expensive, often difficult to scale-up and limited in their design scope compared to traditional roof truss solutions. The strategic aim of the research reported on in this paper was therefore to develop a mass customisable roofing solution to allow the UKäó»s largest roof truss manufacturer to enter into the off-site construction sector without reinventing their business architecture. The research considered both the new build and retrofit market. The first roof solution for the new build market is a äóÖsliding roofäó», a roof truss installation method which includes a pre-prepared system created under factory conditions. The system is delivered to the construction site where it is lifted onto one end of the structure. After the system is in placed it is opened the length of the roof. The second system investigated, to be used for the retrofit market, is a self-supporting and thermally insulated roof panel, designed and developed for a multitude of pitched roofs. Working with the industry partner the suitability of the roof systems as effective off-site solutions has been trialled. The full process was monitored from a design, manufacture and construction perspective with a critical appraisal undertaken for evaluation purposes. These finding are reported.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 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".