{"id":"W4399850394","doi":"10.1109/appeec57400.2023.10561901","title":"Appliance Anomaly Detection as NILM Extention","year":2023,"lang":"en","type":"article","venue":"","topic":"Smart Grid Security and Resilience","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; Memorial University of Newfoundland","funders":"","keywords":"Anomaly detection; Computer science; Anomaly (physics); Artificial intelligence; Computer vision; Physics","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":[0.0004051381,0.0004818662,0.0004484054,0.0009934892,0.0002167316,0.0005532491,0.0009412093,0.0004297886,0.001040266],"category_scores_gemma":[0.001551826,0.0002034281,0.0004193546,0.0006585186,0.0003808743,0.001076534,0.0007858374,0.0006118212,0.0002257934],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007044245,"about_ca_system_score_gemma":0.0004518857,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004389466,"about_ca_topic_score_gemma":0.004510801,"domain_scores_codex":[0.999604,0.00004623353,0.00002117559,0.0001511608,0.0001278051,0.00004953866],"domain_scores_gemma":[0.9994574,0.0001598512,0.0001522911,0.00007688241,0.0001279174,0.00002565374],"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":[0.000250003,0.0001280603,0.02932404,0.0001304581,0.00008955274,0.0004897109,0.0002413509,0.7151108,0.01105491,0.01196442,0.00215457,0.2290622],"study_design_scores_gemma":[0.000001439986,0.00001805383,0.002031171,0.00000450469,0.00000812658,0.00005499031,0.0000167158,0.9934649,0.001289491,0.002522036,0.0005831601,0.000005390524],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1734705,0.0003561585,0.8180292,0.0003601663,0.00008560559,0.00008135865,0.0004206917,0.002627739,0.004568517],"genre_scores_gemma":[0.9698701,0.0001013639,0.02793275,0.0000391836,0.00002146975,0.00003056794,0.0002395376,0.00003208281,0.00173283],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004389466,"threshold_uncertainty_score":0.008727849,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005331054623196559,"score_gpt":0.1999534219675369,"score_spread":0.1946223673443404,"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."}}