Role of risk analysis in fire engineering: a research perspective
Bibliographic record
Abstract
The move of many countries to adopt building and fire regulation based upon outcome or performance based principles is posing some very interesting challenges to the fire research community. Many of the prescriptive solutions upon which the majority of traditional building and fire codes have been based were established over time on the basis of experience. Few of them had any formal measurement of performance and in many cases there was a complete lack of the knowledge required to establish an appropriate measurement criteria. Often, where there were test methods, these did little but result in relative rankings of one solution/product over another and were often only distantly related to the hazard being managed. A good example of this approach is the use of standard fire ratings of assemblies where there is relatively universal agreement that the fire challenge used in the test is rarely realistic in terms of the challenge that the assembly would experience in a 'real' fire today.
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 | 0.083 | 0.061 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.010 | 0.006 |
| Science and technology studies | 0.004 | 0.040 |
| Scholarly communication | 0.026 | 0.034 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.014 | 0.015 |
| Insufficient payload (model declined to judge) | 0.006 | 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".