{"id":"W2160600700","doi":"10.1109/sccc.2005.1587861","title":"A Geometric Framework to Visualize Fuzzy-clustered Data","year":2006,"lang":"en","type":"article","venue":"","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Computer science; Data mining; Fuzzy logic; Cluster analysis; Fuzzy clustering; Visualization; Object (grammar); Artificial intelligence; Scheme (mathematics); Data visualization; Fuzzy set; FLAME clustering; Cluster (spacecraft); Pattern recognition (psychology); Machine learning; 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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003259398,0.0001184608,0.0001209232,0.0003651471,0.00007739397,0.0006217977,0.003823243,0.00003738232,0.00009894783],"category_scores_gemma":[0.00007924614,0.0001021843,0.00002277678,0.002362459,0.00001122679,0.001221071,0.003925867,0.00007233879,0.001123373],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000155637,"about_ca_system_score_gemma":0.00001252945,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000232944,"about_ca_topic_score_gemma":0.00002282522,"domain_scores_codex":[0.9985156,0.0000222216,0.0001934257,0.0006047201,0.0003444615,0.0003195751],"domain_scores_gemma":[0.9975354,0.00008600124,0.00003803015,0.002228088,0.00002812123,0.0000843294],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000002056598,0.0001263719,0.0003559629,0.00001001562,0.00001448566,0.00002662562,0.00002460833,0.00003264679,0.00001274238,0.2939608,0.5000214,0.2054123],"study_design_scores_gemma":[0.0004714809,0.0001237175,0.01365819,0.00003219902,0.00001605717,0.000006200006,0.00002714093,0.08111195,0.0002116051,0.04056083,0.8630878,0.0006928745],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0003907881,0.00005123511,0.9652882,0.0022187,0.0004015769,0.000165335,0.00001907223,0.0003007132,0.03116438],"genre_scores_gemma":[0.07286779,0.000008339298,0.9131662,0.003082829,0.0003767284,0.0000107054,0.0001150316,0.00001311539,0.01035926],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3630664,"threshold_uncertainty_score":0.9996544,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04133289703896613,"score_gpt":0.3064629536711043,"score_spread":0.2651300566321382,"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."}}