{"id":"W2752082125","doi":"10.1080/00207543.2017.1370148","title":"Dynamic risk assessment of complex systems using FCM","year":2017,"lang":"en","type":"article","venue":"International Journal of Production Research","topic":"Cognitive Science and Mapping","field":"Computer Science","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Risk analysis (engineering); Complex system; Set (abstract data type); Computer science; Risk assessment; Risk management; Fuzzy cognitive map; Fuzzy logic; Fuzzy set; Artificial intelligence; Business; Computer security; Membership function","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001393713,0.001196618,0.0009071222,0.004111798,0.0009001919,0.001933363,0.001432723,0.001262487,0.002064957],"category_scores_gemma":[0.004296103,0.0004005603,0.001624059,0.002499412,0.0005689678,0.0013117,0.001322266,0.0009121608,0.0001703709],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002219829,"about_ca_system_score_gemma":0.001666808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04115513,"about_ca_topic_score_gemma":0.01445888,"domain_scores_codex":[0.9992915,0.0001831052,0.00004129478,0.0001165428,0.0002758555,0.00009150915],"domain_scores_gemma":[0.9984635,0.00099033,0.000153326,0.00007569932,0.0002676142,0.00004962007],"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":[0.00002531867,0.00002063336,0.00147017,0.00006870027,0.00007189592,0.0001089166,0.0001217251,0.9569021,0.00062465,0.007244872,0.0002693803,0.03307163],"study_design_scores_gemma":[0.000001552533,0.00000775299,0.0003077463,0.00001017262,0.00001118779,0.00001837636,0.00004243974,0.9933327,0.00018581,0.005664261,0.0004098386,0.000008187532],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05975274,0.0005658613,0.9336299,0.0001987592,0.00003606693,0.000104014,0.0002121862,0.0003075229,0.005192942],"genre_scores_gemma":[0.8370693,0.0005527028,0.1602732,0.00003666586,0.00003619827,0.0001834708,0.0002399361,0.00004108414,0.001567364],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04115513,"threshold_uncertainty_score":0.08183116,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2972341861694459,"score_gpt":0.5413051657991051,"score_spread":0.2440709796296593,"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."}}