Importance Indices in Fire Hazard Problems
Bibliographic record
Abstract
This article investigates a centrality measure, called "Fire Evacuation Importance (FEI)" for building evacuation problems in the event of a fire hazard. This measure provides the probability of a node to be on evacuation routes to the exit and it is a modification of the classical centrality betweenness index. The FEI index is firstly introduced in the static case. An O(n · m + n2 · log n) algorithm is presented for this index, which is based on an All-to-All shortest path adapted computation. Then the dynamic FEI index is introduced for the evacuation routes based on the dynamic model presented by Tabirca et al. [2009]. The dynamic FEI computation is developed by using an adapted algorithm for the dynamic shortest paths. The article also introduces the vitality FEI index to measure how vital each node is for the evacuation. This is done by measuring the change in the overall FEI index when a node is removed from the dynamic network. Finally, two scenarios are presented to apply the FEI indices to some evacuation problems. These are then applied to a practical problem concerning the evacuation of a large building.
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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 | 0.000 |
| 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".