{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.001249449,0.0003746131,0.0005722687,0.0002261274,0.0003815498,0.0003492721,0.0029982,0.00008797894,0.00001849859],"category_scores_gemma":[0.0001654331,0.0003151953,0.0001024128,0.0004673195,0.0002003556,0.003246274,0.01558232,0.0002762846,0.0001242306],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006526555,"about_ca_system_score_gemma":0.0001208292,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008572723,"about_ca_topic_score_gemma":0.00009555346,"domain_scores_codex":[0.9970751,0.0002733188,0.0006131985,0.001249951,0.0002089093,0.0005795358],"domain_scores_gemma":[0.9964978,0.0001803237,0.0001862953,0.002831871,0.00007036999,0.0002333453],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006613664,0.0002984927,0.0007937707,0.0006553823,0.00004833922,0.0001500915,0.007479899,0.000005711416,0.0002462685,0.000263545,0.007463695,0.9825287],"study_design_scores_gemma":[0.001571717,0.0008989761,0.002683229,0.007354008,0.0001017259,0.000534586,0.001346366,0.9414206,0.0008216036,0.001104654,0.04011967,0.002042859],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006676279,0.01631011,0.9686033,0.0001469664,0.0008680844,0.0004533319,0.00005175355,0.0002121513,0.006678066],"genre_scores_gemma":[0.3157856,0.004738836,0.6746106,0.000310734,0.0006231533,0.0002075017,0.0003054043,0.0001246883,0.003293408],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9804858,"threshold_uncertainty_score":0.99993,"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."}}