{"id":"W4405197085","doi":"10.1007/s13753-024-00597-z","title":"Probabilistic Seismic Hazard Assessment for the North China Plain Earthquake Belt: Sensitivity of Seismic Source Models and Ground Motion Prediction Equations","year":2024,"lang":"en","type":"article","venue":"International Journal of Disaster Risk Science","topic":"Seismic Performance and Analysis","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Institute of Engineering Mechanics, China Earthquake Administration; China Earthquake Administration","keywords":"Seismic hazard; Induced seismicity; Seismology; Geology; Earthquake scenario; Hazard; Incremental Dynamic Analysis; Strong ground motion; Uncertainty quantification; Hazard analysis; Seismic risk; Ground motion; Statistics; Engineering; Mathematics; Reliability engineering","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":[0.001554399,0.0005730366,0.0003161076,0.0004640157,0.0002186265,0.0004652033,0.0006068766,0.0004919068,0.000600749],"category_scores_gemma":[0.002974467,0.0002947859,0.0006442681,0.0003201294,0.0003264374,0.0007490308,0.0008381003,0.0005002901,0.00005531827],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007542263,"about_ca_system_score_gemma":0.0008880511,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02108992,"about_ca_topic_score_gemma":0.008269791,"domain_scores_codex":[0.9995406,0.0001939464,0.00002530919,0.0001011379,0.00009086747,0.00004818007],"domain_scores_gemma":[0.9991319,0.0005072224,0.0001202251,0.00007056859,0.0001403764,0.00002981657],"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":[0.00002528301,0.0000156021,0.005033242,0.000008026517,0.00002604794,0.00002882711,0.00001223707,0.9896935,0.0004635276,0.000509438,0.00004210872,0.004142151],"study_design_scores_gemma":[0.000001982992,0.000007288092,0.0007579331,6.48279e-7,0.000003479341,0.000003081946,0.000004130775,0.9989017,0.0001168203,0.0001835818,0.00001733224,0.000001929563],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.792285,0.0001378542,0.2052902,0.0002408403,0.00002177246,0.00004598991,0.0001902279,0.0001408529,0.001647267],"genre_scores_gemma":[0.9950054,0.00002622336,0.004679124,0.000009692499,0.000004138069,0.00001234541,0.00005691466,0.000004105663,0.0002020758],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02108992,"threshold_uncertainty_score":0.04193431,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01342956430987688,"score_gpt":0.2585374264180734,"score_spread":0.2451078621081965,"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."}}