{"id":"W4311892911","doi":"10.1785/0120220138","title":"A Simplified Method for Performing Vector-Valued Probabilistic Seismic Hazard Analysis","year":2022,"lang":"en","type":"article","venue":"Bulletin of the Seismological Society of America","topic":"Seismic Performance and Analysis","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; University of Waterloo","funders":"","keywords":"Fragility; Seismic hazard; Incremental Dynamic Analysis; Hazard; Probabilistic logic; Computer science; Seismology; Reliability engineering; Ground motion; Geology; Engineering; Artificial intelligence; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006145717,0.0002027403,0.0006903963,0.00005502782,0.0002984358,0.000008369399,0.0005790684,0.00007625222,0.0006787773],"category_scores_gemma":[0.00008319201,0.000149745,0.001566348,0.0009882617,0.0001992769,0.00001283172,0.0002371899,0.0002901221,0.000002923002],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000112831,"about_ca_system_score_gemma":0.00002676752,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004051501,"about_ca_topic_score_gemma":1.16928e-7,"domain_scores_codex":[0.9984134,0.0001287147,0.0004910326,0.0002744806,0.0003497828,0.0003425734],"domain_scores_gemma":[0.9989252,0.0003216596,0.0002339569,0.0004024007,0.00006612153,0.0000506269],"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":[0.00003811597,0.00008652996,0.0002806063,0.0001314038,0.001346333,2.562442e-7,0.0004629786,0.9595374,0.0006480156,0.00004984419,0.03052166,0.006896795],"study_design_scores_gemma":[0.0002662761,0.0001466114,0.0007723522,0.000006459827,0.0008168573,0.000002947184,0.0008825179,0.7720504,0.0005606942,0.0003775105,0.2239406,0.0001767385],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3231835,0.000604161,0.6575961,0.01605015,0.0002624201,0.0009968213,0.0002604331,0.0002794313,0.0007670583],"genre_scores_gemma":[0.9414338,0.00004825724,0.05205053,0.005760556,0.00004708231,0.0001684727,0.00003121282,0.00002591457,0.0004342167],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6182503,"threshold_uncertainty_score":0.7432136,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01401424478451673,"score_gpt":0.2436054870479251,"score_spread":0.2295912422634084,"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."}}