{"id":"W2915001123","doi":"10.1609/aaai.v26i1.8282","title":"Weighted Clustering","year":2021,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence","topic":"Advanced Clustering Algorithms Research","field":"Computer Science","cited_by":48,"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; Correlation clustering; CURE data clustering algorithm; Generalization; Single-linkage clustering; Data mining; Canopy clustering algorithm; Artificial intelligence; Fuzzy clustering; Consensus clustering; Hierarchical 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":[0.006395722,0.001460419,0.001415054,0.00389296,0.001536864,0.003971539,0.004711466,0.001943633,0.005613062],"category_scores_gemma":[0.02489288,0.0007017844,0.001564342,0.005369802,0.001964988,0.005894617,0.004100658,0.001946289,0.00259355],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00200571,"about_ca_system_score_gemma":0.002018805,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002463735,"about_ca_topic_score_gemma":0.003453976,"domain_scores_codex":[0.9902273,0.003115044,0.0004975833,0.002656668,0.003027381,0.0004760414],"domain_scores_gemma":[0.9873573,0.004378977,0.001104795,0.004134919,0.002635649,0.0003883849],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001669912,0.0001476887,0.002704565,0.0006095351,0.0004208974,0.0001656261,0.0004031016,0.1679409,0.004662048,0.5719521,0.01687911,0.2339476],"study_design_scores_gemma":[0.00003181117,0.00009386971,0.0009229043,0.000082447,0.00008840288,0.0002602985,0.0001677337,0.4911689,0.004103024,0.4674782,0.03555128,0.00005122693],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006224465,0.0005162205,0.9872662,0.0002992848,0.0001189426,0.0001492216,0.0003256227,0.0002482692,0.004851777],"genre_scores_gemma":[0.2049863,0.001357352,0.7757124,0.000664753,0.0004154058,0.0006055365,0.002702457,0.0004965924,0.01305915],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006395722,"threshold_uncertainty_score":0.03382427,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08640250646346599,"score_gpt":0.3281925805231471,"score_spread":0.2417900740596812,"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."}}