Seismic Resilience Assessment in Optimally Integrated Retrofitting of Existing School Buildings in Italy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Modern society requires that structures exhibit greater levels of resilience, especially under earthquakes. The seismic resilience of buildings is thus gaining increased attention as a particular, beyond-code approach. Seismically retrofitted buildings behave satisfactorily under expected earthquake scenarios; however, this does not guarantee operativity after a seismic event. This study critically reviews several methods currently available in the literature that quantify the seismic resilience level of buildings from different perspectives. An existing reinforced concrete school building, retrofitted according to four distinct strategies, is first evaluated in terms of seismic resilience levels. The overview and critical analysis of available resilience assessment frameworks determine the most suitable parameters to measure the seismic resilience for buildings. Subsequently, this metric is incorporated as an additional decision variable into an integrated seismic and energy retrofitting set of strategies. A multicriteria decision-making analysis is performed to select the optimally combined seismic and energy retrofitting alternative under social, technical, environmental evaluation, and seismic resilience aspects. We show how resilience impacts the preference for integrated seismic and energy retrofitting strategies, especially when this metric is considered as an annualized expected value.
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.
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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it