{"id":"W2557943417","doi":"10.1139/cjce-2015-0411","title":"Hierarchical seismic vulnerability assessment of power transmission systems: sensitivity analysis of fragility curves and clustering algorithms","year":2016,"lang":"en","type":"article","venue":"Canadian Journal of Civil Engineering","topic":"Power System Reliability and Maintenance","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Fragility; Cluster analysis; Sensitivity (control systems); Vulnerability assessment; Algorithm; Computer science; Robustness (evolution); Context (archaeology); Data mining; Hierarchical clustering; Vulnerability (computing); Identification (biology); Mathematics; Engineering; Machine learning; Geology; Physics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.001690295,0.0001874314,0.0007864865,0.0004878713,0.00002787559,0.00001329991,0.0001301635,0.000106094,0.0000305992],"category_scores_gemma":[0.0001926296,0.0001465443,0.0002149343,0.0003951573,0.0000930947,0.0002026578,0.00001282047,0.0002476533,9.95934e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000261945,"about_ca_system_score_gemma":0.0002116293,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000752131,"about_ca_topic_score_gemma":0.005219945,"domain_scores_codex":[0.9983646,0.0001141533,0.0008127773,0.0001604074,0.0002407907,0.0003072314],"domain_scores_gemma":[0.9985788,0.0003197033,0.0001489245,0.0002672647,0.0002117034,0.0004736304],"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":[0.00001013045,0.00002238267,0.01384988,0.002636688,0.0009603791,0.00005588132,0.0004136338,0.966033,0.01368799,0.0001084008,0.0001095727,0.002112037],"study_design_scores_gemma":[0.0004034404,0.00008986906,0.1338665,0.002955168,0.000317832,0.00009197743,0.000047224,0.8600966,0.0007518991,0.00001796778,0.001097559,0.0002639031],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2855816,0.002227374,0.711271,0.0001196074,0.0004110014,0.0001170177,0.00009546857,0.00001881041,0.0001581402],"genre_scores_gemma":[0.9992274,0.0001931424,0.0005203655,0.000007444385,0.00002456297,0.000002203165,0.000001066932,0.00001825199,0.000005570147],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7136458,"threshold_uncertainty_score":0.5975901,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006814323945972186,"score_gpt":0.2137888566949677,"score_spread":0.2069745327489955,"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."}}