Seismic vulnerability analysis in urban systems and road networks. Application to the city of Thessaloniki, Greece
Bibliographic record
Abstract
During the last decades, the aggregation of human, financial and environmental losses related to natural disasters has been increased, constituting a principal threat for the function of modern society. The present paper proposes an integrated methodology for the seismic risk management in urban areas, focused on urban planning and sustainable development. In this framework, the key elements for the urban vulnerability analysis during the crisis, restoration and especially pre-earthquake period are given. A method for the seismic risk analysis of urban roads is also described as the transportation network is of vital importance in case of emergency. The procedure is illustrated through a pilot application to the center of Thessaloniki city, which is an area that concentrates a variety of activities and is characterized by high seismicity. The urban vulnerability is estimated based on a value analysis of the exposed elements at risk, while the functionality of roads is evaluated after the estimation of indirect closures due to possible collapses of adjacent buildings.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".