{"id":"W4383163694","doi":"10.1016/j.epsr.2023.109644","title":"Non-intrusive load monitoring: Comparative analysis of transient state clustering methods","year":2023,"lang":"en","type":"article","venue":"Electric Power Systems Research","topic":"Smart Grid Energy Management","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Cluster analysis; Computer science; Transient (computer programming); Data mining; Algorithm; Data stream clustering; Correlation clustering; CURE data clustering algorithm; Artificial intelligence","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":[0.002868387,0.0006121201,0.0008409507,0.002022281,0.000380455,0.0008039001,0.0010538,0.000579464,0.00122162],"category_scores_gemma":[0.009831851,0.0001921373,0.0005257966,0.001620582,0.0002902876,0.001277047,0.0005919481,0.0004160084,0.0002349305],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006660498,"about_ca_system_score_gemma":0.0005358073,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004663531,"about_ca_topic_score_gemma":0.005514442,"domain_scores_codex":[0.998508,0.0007017907,0.00007169247,0.00015089,0.0004802547,0.00008732194],"domain_scores_gemma":[0.9892024,0.008100229,0.0004508306,0.0007544436,0.001367213,0.0001248161],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.003266935,0.0006722956,0.0211068,0.0007495084,0.0006311467,0.00009477073,0.0005407839,0.2757991,0.01090124,0.006654548,0.00165425,0.6779287],"study_design_scores_gemma":[0.00003332285,0.0003316527,0.01703991,0.00002988343,0.0001323327,0.00009728864,0.0001463797,0.9750378,0.005147671,0.001308137,0.0006690671,0.00002647177],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3979042,0.003057626,0.5907271,0.0002303531,0.0001045222,0.0002019049,0.0002753429,0.001241223,0.006257644],"genre_scores_gemma":[0.9403226,0.0006806417,0.05731203,0.00002454,0.00004794501,0.00005390237,0.0002671695,0.00007466522,0.001216404],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004663531,"threshold_uncertainty_score":0.01516962,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07768111925133246,"score_gpt":0.4038298559469589,"score_spread":0.3261487366956264,"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."}}