Probabilistic seismic risk assessment of India
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
This study presents a comprehensive open probabilistic seismic risk model for India. The proposed model comprises a nationwide residential and non‐residential building exposure model, a selection of analytical seismic vulnerability functions tailored for Indian building classes, and the open implementation of an existing probabilistic seismic hazard model for India. The vulnerability of the building exposure is combined with the seismic hazard using the stochastic (Monte Carlo) event‐based calculator of the OpenQuake engine to estimate probabilistic seismic risk metrics such as average annual economic losses and the exceedance probability curves at the national, state, district, and subdistrict levels. The risk model and the underlying datasets, along with the risk metrics calculated at different scales, are intended to be used as tools to quantitatively assess the earthquake risk across India and also compare with other countries to develop risk‐informed building design guidelines, for more careful land‐use planning, to optimize earthquake insurance pricing, and to enhance general earthquake risk awareness and preparedness.
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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 it