{"id":"W4293704402","doi":"10.1109/tsg.2022.3202926","title":"A Novel ZSV-Based Detection Scheme for FDIAs in Multiphase Power Distribution Systems","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Smart Grid","topic":"Smart Grid Security and Resilience","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"False alarm; Electric power system; Voltage; Mathematics; Algorithm; Power (physics); Control theory (sociology); Computer science; Engineering; Statistics; Artificial intelligence; Electrical engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002439327,0.0001803032,0.0001798088,0.0002069056,0.0003539698,0.00003189357,0.0001297576,0.0000874812,0.00004472731],"category_scores_gemma":[0.000007507487,0.0002058406,0.0001337766,0.0004387186,0.00003170907,0.0001270452,0.000001091815,0.0004162467,0.00001346985],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003949037,"about_ca_system_score_gemma":0.00003693087,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001367122,"about_ca_topic_score_gemma":0.0002136851,"domain_scores_codex":[0.9988469,0.00003953076,0.0002890332,0.0002631355,0.0002436457,0.0003177209],"domain_scores_gemma":[0.9994932,0.0001354344,0.00003223235,0.0002237697,0.00003534928,0.0000799796],"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":[0.0001586425,0.0003235035,0.0000200668,0.00006380975,0.00002024517,0.000003940386,0.000122363,0.9594741,0.03901165,0.00001188858,0.0002442197,0.000545607],"study_design_scores_gemma":[0.002274456,0.0002887561,0.0002732988,0.00003584063,0.00002091105,0.00002574916,0.0002747326,0.9083226,0.06425603,0.00000279682,0.02388865,0.000336151],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2102604,0.00006536944,0.7823422,0.00004197406,0.005496109,0.0005789812,0.0009448021,0.0002458564,0.00002435636],"genre_scores_gemma":[0.9984881,0.000006723852,0.0002646013,0.00003645736,0.00008982021,0.0009904811,0.00005529251,0.00003300886,0.00003548447],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7882278,"threshold_uncertainty_score":0.8393936,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01347069672916393,"score_gpt":0.218567502169829,"score_spread":0.2050968054406651,"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."}}