Design rules to improve efficiency in the steel construction industry
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
In steel construction projects, 88% of total decisions impacting cost are made during the design phase. These decisions are made by design professionals, who have neither the knowledge nor the experience of manufacturing operations. In manufacturing engineering, collaboration between designers and manufacturers is well established and formalized through different methods and design rules such as design for manufacturing and assembly (DFMA). These rules provide designers with essential knowledge to reduce the cost and time of manufacturing and assembly of parts during their design, while increasing customer satisfaction Building Information Modeling (BIM) and TFV Theory (Transformation Flow and Value) provide to the construction industry, tools and processes to improve collaboration between design and manufacturing phases while reducing waste during projects. However, BIM and TFV theory do not formalize collaboration between designers and manufacturers of steel structures. Yet, the lack of collaboration between these two phases causes lot of rework, lot of waste of time and material during projects.
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.
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 it