{"id":"W1987111416","doi":"10.1002/widm.30","title":"Density‐based clustering","year":2011,"lang":"en","type":"article","venue":"Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery","topic":"Advanced Clustering Algorithms Research","field":"Computer Science","cited_by":810,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Cluster analysis; Outlier; Data set; Computer science; Data mining; Cluster (spacecraft); Set (abstract data type); Single-linkage clustering; DBSCAN; Pattern recognition (psychology); 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":[0.00340053,0.001490543,0.002054716,0.008395691,0.002071257,0.004955584,0.003101084,0.002351815,0.008533414],"category_scores_gemma":[0.01720308,0.0009357687,0.001820197,0.009168972,0.001702363,0.003516115,0.0035317,0.001822484,0.006697941],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002795575,"about_ca_system_score_gemma":0.002694284,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008082308,"about_ca_topic_score_gemma":0.004981634,"domain_scores_codex":[0.9950125,0.001133185,0.0002726587,0.001141866,0.002168474,0.0002712706],"domain_scores_gemma":[0.9942855,0.001876517,0.0004751302,0.001232438,0.001974573,0.0001558221],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002393312,0.0001253394,0.007886333,0.001176343,0.0005308698,0.0003195677,0.0009416512,0.2643835,0.004868445,0.2815238,0.06140286,0.376602],"study_design_scores_gemma":[0.00003969035,0.00006405476,0.003796205,0.000299132,0.0001236625,0.0006647286,0.0003861445,0.6702391,0.006034456,0.222713,0.09544726,0.0001926038],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006066402,0.002601064,0.9721345,0.000663111,0.0002246034,0.0003432082,0.001502978,0.001607541,0.01485662],"genre_scores_gemma":[0.3066771,0.005878679,0.6572748,0.0006545893,0.0004974403,0.0007769049,0.009142983,0.001007373,0.01809016],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008533414,"threshold_uncertainty_score":0.02854711,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1565194252285615,"score_gpt":0.3728985120791855,"score_spread":0.216379086850624,"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."}}