{"id":"W4241584538","doi":"10.1109/isci53438.2021.00013","title":"RiskISM: A Risk Assessment Tool for Substations","year":2021,"lang":"en","type":"article","venue":"","topic":"Smart Grid Security and Resilience","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Downtime; Failure mode, effects, and criticality analysis; Computer science; Criticality; Reliability engineering; Risk assessment; Visualization; Identification (biology); Risk analysis (engineering); Computer security; Engineering; Data mining; Failure mode and effects analysis","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":[0.00006074294,0.00004958462,0.00005909927,0.0000169982,0.00007446305,0.00002949574,0.00004180353,0.00002848637,0.0001734614],"category_scores_gemma":[0.00003654907,0.00004620671,0.00004294543,0.00009472026,0.000008954327,0.00006916035,0.000008376805,0.00006864952,0.00002085131],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001888678,"about_ca_system_score_gemma":0.00002607275,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005640269,"about_ca_topic_score_gemma":0.00009571981,"domain_scores_codex":[0.9996403,0.00000955433,0.00008765126,0.00008372166,0.00006247347,0.0001163221],"domain_scores_gemma":[0.9997013,0.0001072804,0.000007106971,0.0001122715,0.00004467497,0.00002732206],"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":[0.00001598923,0.0004528007,0.04999833,0.0005433715,0.0005169303,0.00007085981,0.003804437,0.4453097,0.02427692,0.2125544,0.2174276,0.04502871],"study_design_scores_gemma":[0.001119274,0.00004987979,0.1055908,0.0000265312,0.00008235937,0.00001876537,0.0009716882,0.6616387,0.04089179,0.009048576,0.1800172,0.0005444654],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3818268,0.0002824373,0.6009424,0.0001991619,0.0006994001,0.0001766516,0.00005982393,0.0002799297,0.01553341],"genre_scores_gemma":[0.9566599,0.0003030237,0.04205139,0.00006231378,0.00009325381,0.00006056941,0.0000230252,0.00001106712,0.0007354363],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5748331,"threshold_uncertainty_score":0.189928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007270698995584531,"score_gpt":0.2508006849538263,"score_spread":0.2435299859582418,"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."}}