{"id":"W2125824025","doi":"10.14288/1.0073795","title":"Seismic risk assessment of high-voltage transformers using Bayesian belief networks","year":2013,"lang":"en","type":"article","venue":"cIRcle (University of British Columbia)","topic":"Seismic Performance and Analysis","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Transformer; Probabilistic logic; Reliability engineering; Engineering; Voltage; Vulnerability assessment; High voltage; Computer science; Electrical engineering; Artificial intelligence","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":[0.0001027123,0.00005751856,0.0003246996,0.00007264641,0.0001353848,0.00004263472,0.0002029982,0.0001074621,0.0002705512],"category_scores_gemma":[0.00000185525,0.0001888767,0.0001615151,0.0003503095,0.0001134875,0.000506505,0.00002721943,0.0001776967,0.000004953364],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008727763,"about_ca_system_score_gemma":0.00003061708,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1912577,"about_ca_topic_score_gemma":0.02394168,"domain_scores_codex":[0.9991875,0.00001800355,0.0001702454,0.0001849616,0.0001769482,0.0002623092],"domain_scores_gemma":[0.9995412,0.00001785763,0.00008690336,0.0001773048,0.00008360883,0.0000930848],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000001467416,0.00005905642,0.03681807,0.0001393142,0.0002876872,0.00001441248,0.0001217103,0.3842272,0.0008257212,3.552475e-7,0.00114638,0.5763586],"study_design_scores_gemma":[0.0003066069,0.00001786864,0.4759649,0.00006165003,0.00008344342,0.000004584272,0.0004602245,0.5229288,0.000002063173,0.00003403116,0.00002638885,0.0001093569],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7628117,0.00008305952,0.236344,0.000007585139,0.00007417532,0.0001101333,0.00005424062,0.00005793841,0.000457117],"genre_scores_gemma":[0.9979149,0.0007434136,0.001182801,0.00001611113,0.00002656646,4.503935e-7,0.00002167661,0.0000186967,0.00007535973],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5762492,"threshold_uncertainty_score":0.9938688,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004140910940632988,"score_gpt":0.1650578486936488,"score_spread":0.1609169377530158,"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."}}