{"id":"W2950793146","doi":"10.2298/csis180601007l","title":"Density-based clustering with constraints","year":2019,"lang":"en","type":"article","venue":"Computer Science and Information Systems","topic":"Advanced Clustering Algorithms Research","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"DBSCAN; Cluster analysis; Computer science; Benchmark (surveying); Data mining; Process (computing); Computation; Correlation clustering; Quality (philosophy); Constrained clustering; Algorithm; CURE data clustering algorithm; Machine learning","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":[0.003018604,0.001459423,0.002290423,0.003562935,0.001282993,0.003077802,0.00430308,0.001749145,0.003127632],"category_scores_gemma":[0.01781444,0.0009369347,0.001431763,0.005716801,0.001255674,0.003189018,0.003165681,0.002226444,0.001506454],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002544832,"about_ca_system_score_gemma":0.002869155,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01735226,"about_ca_topic_score_gemma":0.01174126,"domain_scores_codex":[0.9949393,0.00112419,0.0003161964,0.0009122042,0.002473637,0.0002343828],"domain_scores_gemma":[0.9942403,0.002514816,0.0004005083,0.00101444,0.00167663,0.0001533951],"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":[0.0001957015,0.00008578829,0.001729179,0.000437513,0.0001756488,0.00009612517,0.0002345045,0.6582664,0.002245583,0.06567695,0.007550555,0.2633061],"study_design_scores_gemma":[0.00001784605,0.00002233353,0.0002842175,0.00003060339,0.00001759912,0.00009052709,0.00004993934,0.9622611,0.001934312,0.03014092,0.005121072,0.00002959993],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003420444,0.0003219233,0.9939528,0.0001048702,0.0000282228,0.0001056532,0.00020255,0.0005213053,0.00134226],"genre_scores_gemma":[0.09173143,0.0005484438,0.9035524,0.0001725622,0.00007186201,0.0003177419,0.001514309,0.0002983863,0.00179285],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01735226,"threshold_uncertainty_score":0.03450251,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01108352661053865,"score_gpt":0.2395449261787232,"score_spread":0.2284613995681846,"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."}}