A Survey on Contemporary Practices for Achieving Structural Robustness in Mass Timber Buildings
Bibliographic record
Abstract
This paper summarises the contemporary practices and implementations of existing codes and guidelines with respect to disproportionate collapse prevention as discussed in detail in Mpidi Bita et al. [1]. Focus is given on structural robustness, defined as the ideal method to decrease the probability of disproportionate collapse in buildings following an initial damage. The results from a global survey with 171 participants (mainly structural engineers) are presented. By comparing practices applied to different structural materials (steel, concrete and timber) and in different regions (Canada, USA, Europe, Australia/New Zealand), areas of improvements for the existing codes and guidelines as well as further research are identified. The results emphasise on the importance of including specific recommendations for structural robustness in building codes, applicable to high importance and high occupancy structures. A performance-based approach is preferable, rather than prescriptive requirements, for practical and economical solutions. In addition, the obtained responses highlight the need to further develop the existing indirect and direct methods for disproportionate collapse prevention and structural robustness to include material-specific considerations.
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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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".