{"id":"W3089119772","doi":"10.1177/8755293020957374","title":"Probabilistic seismic risk assessment of India","year":2020,"lang":"en","type":"article","venue":"Earthquake Spectra","topic":"Seismic Performance and Analysis","field":"Engineering","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Seismic risk; Probabilistic logic; Earthquake scenario; Vulnerability (computing); Hazard; Seismic hazard; Risk assessment; Probabilistic risk assessment; Urban seismic risk; Preparedness; Risk analysis (engineering); Computer science; Engineering; Civil engineering; Business; Computer security; Economics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005599692,0.0007640524,0.0004572983,0.001011457,0.0003517433,0.001678657,0.001433624,0.0006199205,0.002115643],"category_scores_gemma":[0.001785586,0.0004229514,0.001004994,0.001106176,0.0007115134,0.001164279,0.001555562,0.0006860652,0.000392992],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001726056,"about_ca_system_score_gemma":0.001303144,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03108766,"about_ca_topic_score_gemma":0.01387559,"domain_scores_codex":[0.9994925,0.0001396171,0.00003007808,0.00008451252,0.0001623105,0.00009105316],"domain_scores_gemma":[0.9993106,0.0002851604,0.0001182309,0.00008987093,0.0001628899,0.0000333163],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001538048,0.00001048348,0.002341073,0.00001593388,0.00002003989,0.00008330926,0.00005141765,0.9734251,0.0002275188,0.01870537,0.000752582,0.00435173],"study_design_scores_gemma":[0.000005128067,0.00002425801,0.002724251,0.00001115134,0.00002272212,0.0001257025,0.00008701055,0.9730699,0.0002184766,0.02099378,0.002690438,0.00002725191],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3661615,0.0008330554,0.5418793,0.001864591,0.00008852843,0.0001797284,0.005319533,0.001388969,0.08228491],"genre_scores_gemma":[0.9835724,0.000390046,0.009274426,0.0000618802,0.00002271908,0.00007177614,0.001020868,0.00005714934,0.005528675],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03108766,"threshold_uncertainty_score":0.06181341,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008485357971048808,"score_gpt":0.2163914709987405,"score_spread":0.2079061130276917,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}