{"id":"W3211022704","doi":"10.1109/ccece53047.2021.9569097","title":"Anomaly Detection on Smart Meters Using Hierarchical Self Organizing Maps","year":2021,"lang":"en","type":"article","venue":"","topic":"Electricity Theft Detection Techniques","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Anomaly detection; Metering mode; Smart meter; Computer science; Anomaly (physics); Smart grid; Automatic meter reading; Data mining; Artificial intelligence; Real-time computing; Engineering; Telecommunications; 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":[0.0001149271,0.0001467664,0.0001429046,0.0002034155,0.00009569247,0.00006065932,0.00007370605,0.0001161763,0.00009341603],"category_scores_gemma":[0.00004762777,0.000160194,0.00006284239,0.0006412963,0.00001003355,0.0001220755,0.00002435344,0.0003577938,0.00003999091],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002808925,"about_ca_system_score_gemma":0.00002131908,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003743195,"about_ca_topic_score_gemma":0.00004901903,"domain_scores_codex":[0.999165,0.00005249394,0.0001775706,0.0002038283,0.0001533007,0.0002478263],"domain_scores_gemma":[0.9995943,0.00006073577,0.00001649427,0.0002125511,0.00004990082,0.00006607595],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000005962866,0.00002705744,0.0001425173,0.0000286161,0.00006399926,0.00002639289,0.00007978515,0.001121603,0.9840747,0.0001918471,0.0001221729,0.01411533],"study_design_scores_gemma":[0.00009593055,0.00006013189,0.0001582484,0.00001234079,0.00001687582,0.0001001028,0.00001668624,0.03705247,0.960401,0.0003547933,0.001548875,0.000182536],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7677032,0.0000370295,0.2211387,0.00004601907,0.0003025209,0.0001004968,0.000001303355,0.003441464,0.007229197],"genre_scores_gemma":[0.9785731,0.00002071195,0.02100533,0.0001295816,0.00007621832,0.000005624639,0.000001799418,0.00005530662,0.0001323582],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2108698,"threshold_uncertainty_score":0.6532523,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01021022196509834,"score_gpt":0.2066924567307587,"score_spread":0.1964822347656603,"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."}}