{"id":"W2103535650","doi":"10.1109/tsmcb.2005.863371","title":"Rough–Fuzzy Collaborative Clustering","year":2006,"lang":"en","type":"article","venue":"IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":258,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Cluster analysis; Data mining; Partition (number theory); Fuzzy clustering; Computer science; Fuzzy logic; Cluster (spacecraft); Measure (data warehouse); Consensus clustering; Artificial intelligence; Mathematics; CURE data clustering algorithm","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"],"consensus_categories":[],"category_scores_codex":[0.0003137467,0.00050375,0.0005199483,0.0002270463,0.0004298372,0.0007778633,0.0006433115,0.000255687,0.00002192323],"category_scores_gemma":[0.00000328199,0.0004740258,0.0001339758,0.0006445775,0.0001873469,0.0002912967,0.00001948472,0.0003772748,0.0001986546],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001025063,"about_ca_system_score_gemma":0.00007204152,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005635302,"about_ca_topic_score_gemma":0.0004032934,"domain_scores_codex":[0.9968587,0.0002139872,0.0007461718,0.0008975473,0.0005989312,0.0006846992],"domain_scores_gemma":[0.9982746,0.0001603115,0.0002316651,0.0008851345,0.0001905054,0.0002577997],"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":[0.0002814159,0.003269312,0.0007492288,0.0007722876,0.0008096504,0.0005807427,0.008984082,0.5963957,0.002142223,0.2302888,0.04495462,0.110772],"study_design_scores_gemma":[0.006404857,0.002672042,0.003240015,0.0009281157,0.000361233,0.0006661765,0.001308448,0.6063231,0.006115615,0.008813166,0.3585697,0.004597525],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01948579,0.001763164,0.9011777,0.0006965951,0.003911772,0.001179409,0.00009836566,0.000580145,0.07110703],"genre_scores_gemma":[0.9877233,0.0004015837,0.004513289,0.0002091263,0.0003030921,0.0001176113,0.000006458629,0.00005105035,0.006674485],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9682375,"threshold_uncertainty_score":0.9997711,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01446450397479102,"score_gpt":0.2229931761474985,"score_spread":0.2085286721727075,"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."}}