Bibliographic record
Abstract
This document is a critical assessment of building codes and standards pertaining to structural design for fire from the United States, Canada, European Union members, Japan, New Zealand and Australia.These countries were selected because of their vigorous research activities on this topic, and the relevance of their engineering practice to that in the US.In the US, there is a dynamic interplay between various consensus-based code writing bodies (such as the International Building Code), and professional associations (such as the Society of Fire Protection Engineers, the National Fire Protection Association, the American Society for Testing and Materials, the American Society of Civil Engineers, the American Institute for Steel Construction, the American Concrete Institute International, and the Precast/prestressed Concrete Institute), which can produce authoritative and influential guidance documents.It has been necessary to study not just the codes and standards, but also the specifications and guides where applicable.The review presents both prescriptive and performance-based standards, but puts more emphasis on the latter, and topics that are the subject of current research or in need of updating.The structural materials covered are steel, concrete and composites of steel and concrete.The assessment identifies gaps in U.S. codes and standards for the design of structures for fire.
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 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 | 0.011 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.013 | 0.016 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".