{"id":"W4285364251","doi":"10.1609/aaai.v26i1.8282","title":"Weighted Clustering","year":2021,"lang":"en","type":"article","venue":"","topic":"Advanced Clustering Algorithms Research","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Strategic Research Council; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China; National Research Foundation; Sino-Danish Center; Danmarks Grundforskningsfond; National Science Foundation","keywords":"Cluster analysis; Computer science; Generalization; CURE data clustering algorithm; Correlation clustering; Data mining; Single-linkage clustering; Artificial intelligence; Consensus clustering; Hierarchical clustering; Canopy clustering algorithm; Fuzzy clustering; Selection (genetic algorithm); Pattern recognition (psychology); Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006527551,0.001542561,0.001478994,0.00390896,0.001495917,0.003878735,0.004768128,0.001891459,0.005676584],"category_scores_gemma":[0.02547514,0.0007257585,0.001593436,0.005235279,0.001978986,0.005737499,0.004099178,0.001980521,0.002632196],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001988338,"about_ca_system_score_gemma":0.001993049,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0024084,"about_ca_topic_score_gemma":0.003388844,"domain_scores_codex":[0.9900901,0.003124344,0.0004905902,0.002688661,0.00311374,0.0004924854],"domain_scores_gemma":[0.9866412,0.004697418,0.001156429,0.00436612,0.002731978,0.0004068024],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001806301,0.0001545736,0.00270599,0.0006249604,0.0004388449,0.0001612359,0.0003756223,0.1894803,0.004812484,0.5447978,0.0171184,0.2391491],"study_design_scores_gemma":[0.00003116435,0.00009946995,0.0008966582,0.00008124193,0.00008993804,0.0002402717,0.0001512519,0.5285537,0.004069252,0.433836,0.03190219,0.00004894778],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006223437,0.0005139405,0.9874862,0.0002759607,0.0001151616,0.0001471546,0.0003088775,0.0002474963,0.004681703],"genre_scores_gemma":[0.210643,0.001408904,0.7695887,0.0006806934,0.0004407699,0.0006161916,0.002771092,0.00052823,0.01332241],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006527551,"threshold_uncertainty_score":0.03452146,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02217365358364736,"score_gpt":0.2965578701439754,"score_spread":0.274384216560328,"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."}}