Adding value through innovation in structural design: 2 – Innovative design of timber structures
Bibliographic record
Abstract
<p>This short paper will focus on opportunities for innovative thinking in the creation of hybrid structures and how this innovation can add value – the theme of an open forum discussion seminar led by the Institution of Structural Engineers at the 2017 IABSE Symposium in Vancouver.</p> <p>During the past century, steel and concrete have dominated as primary building materials for structural designers. Timber has – for many years – remained the neglected child; when it is used, its design is often relegated to timber manufacturing firms. This paper and subsequent presentation will address emerging factors in our industry that will increase opportunities for structural designers to sensibly introduce wood into their design repertoires, often in combination with steel and concrete, to create functionally and cost‐efficient structures that address the sustainability concerns of our day. Drawing on the collective wisdom of engineers who were ‘out of the box’ thinkers, it will also provide some foundational thought and stimulating discussion that assesses what it takes to become a fresh thinking engineer who considers all material combinations when designing structures.</p>
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".