{"id":"W3201866395","doi":"10.1016/j.knosys.2021.107522","title":"A clustering solution for analyzing residential water consumption patterns","year":2021,"lang":"en","type":"article","venue":"Knowledge-Based Systems","topic":"Water Systems and Optimization","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":false,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"Australian Research Council; Yarra Valley Water; City West Water","keywords":"Cluster analysis; Computer science; Data mining; Data set; Hierarchical clustering; Set (abstract data type); Profiling (computer programming); Machine learning; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003174405,0.0001882186,0.0002685822,0.0001512043,0.0001440093,0.0002044623,0.00008527761,0.0001384903,0.00003511574],"category_scores_gemma":[0.00001161913,0.0001714156,0.0001185062,0.00008075876,0.00001034731,0.000157678,0.00002530396,0.00007964048,0.00012152],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001842185,"about_ca_system_score_gemma":0.0000281758,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004754595,"about_ca_topic_score_gemma":0.001115899,"domain_scores_codex":[0.9987162,0.00009679557,0.0004504544,0.0002650445,0.0001152099,0.0003562465],"domain_scores_gemma":[0.9993688,0.00004206977,0.00004148527,0.0002615397,0.0002104223,0.00007566687],"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":[0.00003887607,0.00006633019,0.00935428,0.007062202,0.0001882059,0.0000227682,0.001461218,0.9034101,0.07170763,0.00005888354,0.005789074,0.0008404623],"study_design_scores_gemma":[0.0008953645,0.00001959866,0.0003752009,0.0004680376,0.00004931136,0.00001418417,0.00004898483,0.95057,0.04328034,0.000002686584,0.004007217,0.0002690564],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06451831,0.001262493,0.9293377,0.00002161637,0.003741005,0.0004230236,0.0000333672,0.0003379333,0.0003245769],"genre_scores_gemma":[0.9972231,0.00001098204,0.0005590079,0.000004427182,0.0006734345,0.000186704,0.0002941654,0.00005987658,0.0009882902],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9327048,"threshold_uncertainty_score":0.6990123,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02324305787918286,"score_gpt":0.2390625346155384,"score_spread":0.2158194767363556,"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."}}