{"id":"W3096040206","doi":"10.1109/spies48661.2020.9243025","title":"Fault Detection in Active Hybrid Distribution Networks: Overcoming Uncertainty","year":2020,"lang":"en","type":"article","venue":"","topic":"Smart Grid Security and Resilience","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Bayesian network; Inference; Fault detection and isolation; Reliability (semiconductor); Representation (politics); Distributed generation; Bayesian probability; Bayesian inference; Graphical model; Fault (geology); Data mining; Task (project management); Artificial intelligence; 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":[0.001408451,0.0005076455,0.0005864171,0.000703383,0.000294004,0.0009544343,0.0007854604,0.000571664,0.0003969018],"category_scores_gemma":[0.005528599,0.0002953939,0.0002677316,0.0005144655,0.000789627,0.001844867,0.00102229,0.0007438191,0.00007373569],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006519166,"about_ca_system_score_gemma":0.0004839607,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003250851,"about_ca_topic_score_gemma":0.002204898,"domain_scores_codex":[0.9992711,0.0002771221,0.00002696867,0.0001390975,0.0002306351,0.00005513395],"domain_scores_gemma":[0.9972396,0.002069106,0.0002722644,0.0001148819,0.0002575865,0.0000466073],"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":[0.0002136044,0.00003896596,0.002281712,0.00009632439,0.00005442027,0.0001413283,0.0001736735,0.8587803,0.005060878,0.02345183,0.0004596293,0.1092473],"study_design_scores_gemma":[0.000005583171,0.00001480653,0.0002639115,0.000005970136,0.000005819531,0.00002716863,0.00001286036,0.9897278,0.0008632434,0.008858512,0.0002082939,0.000006009047],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02115487,0.000176815,0.9778186,0.0001219775,0.000009662767,0.00001154389,0.00001683776,0.0001068559,0.0005829495],"genre_scores_gemma":[0.9437516,0.0002622992,0.0552417,0.00005636709,0.0000298277,0.00002695968,0.0000420092,0.00001949574,0.0005698186],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003250851,"threshold_uncertainty_score":0.007448733,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007172157413042332,"score_gpt":0.1958209797128623,"score_spread":0.18864882229982,"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."}}