{"id":"W2123071949","doi":"10.1109/rams.2007.328048","title":"Fault Tree Analysis Based on Fuzzy Logic","year":2007,"lang":"en","type":"article","venue":"","topic":"Risk and Safety Analysis","field":"Decision Sciences","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Fuzzy logic; Fault tree analysis; Fuzzy set operations; Defuzzification; Computer science; Data mining; Fuzzy classification; Fuzzy number; Artificial intelligence; Neuro-fuzzy; Reliability (semiconductor); Fuzzy set; Machine learning; Fuzzy control system; Reliability engineering; 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":[0.001039295,0.000474151,0.0006406881,0.003423146,0.000659181,0.001213568,0.0007356356,0.0005318649,0.002888863],"category_scores_gemma":[0.00428023,0.0002215424,0.0009738044,0.001743647,0.0004787603,0.001974567,0.0005412362,0.0005948075,0.0003380271],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009668515,"about_ca_system_score_gemma":0.000939528,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004761649,"about_ca_topic_score_gemma":0.00315794,"domain_scores_codex":[0.9991814,0.0001948536,0.00004802709,0.00009582,0.0004234959,0.00005642559],"domain_scores_gemma":[0.998471,0.0010358,0.0001089609,0.00005642183,0.0002964706,0.00003138941],"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":[0.0001305776,0.0000595395,0.001998878,0.0002147525,0.0001091858,0.0003025921,0.0003270294,0.5413989,0.007925004,0.1704361,0.002405287,0.2746921],"study_design_scores_gemma":[0.000006253419,0.00001962616,0.0002959447,0.00001758123,0.00001935299,0.00006017552,0.00002274259,0.9439299,0.001205781,0.05293877,0.001470818,0.0000130241],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007115465,0.0001337686,0.9906985,0.00004716296,0.00001282028,0.00002811495,0.00007841091,0.0001800082,0.001705722],"genre_scores_gemma":[0.4271804,0.0004228383,0.5702012,0.00006454352,0.00005458619,0.0001488502,0.0002895049,0.00005921988,0.001578814],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004761649,"threshold_uncertainty_score":0.009664178,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09041557628782093,"score_gpt":0.3958820098594212,"score_spread":0.3054664335716002,"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."}}