{"id":"W4292491722","doi":"10.1016/j.soildyn.2022.107501","title":"Gaussian random field based correlation model of building seismic performance for regional loss assessment","year":2022,"lang":"en","type":"article","venue":"Soil Dynamics and Earthquake Engineering","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Gaussian random field; Kriging; Random field; Gaussian; Gaussian process; Spatial correlation; Hyperparameter; Kernel (algebra); Gaussian function; Statistical physics; Geology; Computer science; Mathematics; Statistics; Algorithm; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001405602,0.0007265125,0.0009527103,0.0008831031,0.000288333,0.0006865404,0.001716938,0.001358158,0.001535405],"category_scores_gemma":[0.003245905,0.0005237173,0.0009179439,0.001369886,0.000666472,0.001187022,0.0005209998,0.001082367,0.0005952474],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00111833,"about_ca_system_score_gemma":0.001219374,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02369388,"about_ca_topic_score_gemma":0.01866529,"domain_scores_codex":[0.9995671,0.0001207921,0.00001679845,0.0001119095,0.00009654746,0.00008688571],"domain_scores_gemma":[0.998628,0.0007233004,0.0001695465,0.0001232167,0.0003075491,0.0000484209],"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":[0.0000394487,0.00002675801,0.0008056673,0.00001797781,0.00002716552,0.00003465952,0.00001449501,0.9880305,0.0005642551,0.003844255,0.0004461674,0.006148625],"study_design_scores_gemma":[0.000001157149,0.000004983944,0.0002385692,0.000001090842,0.00000444874,0.000005327771,0.000001691031,0.9992094,0.00006194103,0.0004292581,0.00003940149,0.000002723462],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08419906,0.0004033805,0.9122728,0.0001885787,0.00006745749,0.00003812315,0.00039892,0.0005467318,0.001885071],"genre_scores_gemma":[0.9668671,0.0004919168,0.02529315,0.00008569325,0.00005107533,0.0000929146,0.0007575789,0.000077816,0.006282629],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02369388,"threshold_uncertainty_score":0.04711193,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00473014168433502,"score_gpt":0.1937227185908659,"score_spread":0.1889925769065308,"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."}}