Systemic Seismic Vulnerability of Transportation Networks and Emergency Facilities
Bibliographic record
Abstract
In the aftermath of an earthquake, structural damage and debris represent major obstructions to the mobility of evacuees and first responders and to normal economic activities. Few studies have integrated the performance of urban road networks with obstructions from structural damage and its impact on systemic vulnerability toward evacuation and emergency response operations. In this study, procedures to evaluate some of the impacts of debris have been proposed. A probabilistic model is developed and validated to estimate roadside debris generated during an earthquake and to evaluate the impact on systemic vulnerability. LaSalle, a borough of Montreal city, is taken as a case study. Systemic vulnerability of transportation networks and emergency facilities depends on the level of traffic in the road network, roadway capacity, proximity, robustness and redundancy of the emergency facilities, and the vulnerability of the built environment. The results from this analysis can be used to identify critical components and prioritize retrofits to the road network and the localization of emergency facilities and to prepare alternate emergency response plans.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".