{"id":"W2026643052","doi":"10.1007/s11047-009-9173-5","title":"Flocking based approach for data clustering","year":2009,"lang":"en","type":"article","venue":"Natural Computing","topic":"Advanced Clustering Algorithms Research","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Cluster analysis; Computer science; Particle swarm optimization; Fuzzy clustering; Correlation clustering; CURE data clustering algorithm; Data mining; Canopy clustering algorithm; Artificial intelligence; Consensus clustering; 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":[0.001699983,0.0007072415,0.001509876,0.00391337,0.002014264,0.00114393,0.002385685,0.001561461,0.002596368],"category_scores_gemma":[0.005182086,0.0004705577,0.001478227,0.002882161,0.001095075,0.001931071,0.001697236,0.001501089,0.0007621138],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00133367,"about_ca_system_score_gemma":0.001024536,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006989289,"about_ca_topic_score_gemma":0.007150676,"domain_scores_codex":[0.9985745,0.0003851134,0.00009481851,0.000320956,0.0005300054,0.00009458677],"domain_scores_gemma":[0.9981561,0.0006617058,0.0001289398,0.0003497469,0.0006138454,0.00008956667],"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":[0.0003485145,0.0002572472,0.002894684,0.0005285127,0.0004106577,0.0002556814,0.0008503103,0.2502554,0.02131745,0.1217935,0.01085062,0.5902375],"study_design_scores_gemma":[0.00002142241,0.0001123521,0.001090636,0.00003833893,0.00005364423,0.000254866,0.0001240426,0.9450967,0.003612828,0.04332045,0.00623745,0.00003732292],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00535459,0.0002548346,0.9931467,0.00008780608,0.00005975846,0.00008611967,0.00004376595,0.0001758174,0.0007904557],"genre_scores_gemma":[0.14284,0.0004936921,0.8498669,0.0001924894,0.0001240218,0.0003451483,0.0004378137,0.0001188184,0.005581049],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006989289,"threshold_uncertainty_score":0.01389724,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0709870533393512,"score_gpt":0.3606660983964147,"score_spread":0.2896790450570635,"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."}}