Analysis of needs and existing capabilities for full-scale fire resistance testing
Bibliographic record
Abstract
This report uses the term "fire-induced collapse" to indicate the failure of a structure, or significant portion of a structure, that could be attributable directly to a fire event in the building. In some cases, the building may have been under construction or in process of renovation, or it may have experienced significant damage prior to the fire caused by a blast, impact, or an earthquake. A subsequent report on the collapse of the WTC towers (NIST NCSTAR 1, September 2005) found that WTC 1 and WTC 2 collapsed due to aircraft impact damage to the structure and fireproofing as well as to fire. Both effects (damage and fire) were equally important. In the absence of structural and insulation damage, a fire substantially similar to or less intense than the fires encountered on September 11, 2001, likely would not have led to the collapse of a WTC tower. On the other hand, it was concluded in NIST NCSTAR 1A (October, 2008) that WTC 7 would have collapsed from fires having the same characteristics as those experienced on September 11, 2001, even without the initial structural damage to the building initiated by the collapse of WTC 1. The Building Performance Study conducted by the Federal Emergency Management Agency (FEMA 403, May 2002) refers to the partial collapse of WTC 5 as "fire-induced." No analysis was conducted to determine the relative roles of the initial structural damage and the subsequent fires that led to the fate of WTC 5.
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 | 0.010 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.006 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.007 |
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".