{"id":"W2570647573","doi":"10.1016/j.neucom.2017.01.017","title":"Interval kernel Fuzzy C-Means clustering of incomplete data","year":2017,"lang":"en","type":"article","venue":"Neurocomputing","topic":"Rough Sets and Fuzzy Logic","field":"Computer Science","cited_by":59,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"National Natural Science Foundation of China","keywords":"Cluster analysis; Fuzzy clustering; Kernel (algebra); Mathematics; Data mining; Data stream clustering; Computer science; Pattern recognition (psychology); CURE data clustering algorithm; Correlation clustering; Constrained clustering; 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":["open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.0004475308,0.0001614308,0.0002623126,0.00006374917,0.0004742997,0.0004496824,0.006247743,0.00004308767,0.000002774709],"category_scores_gemma":[0.0001417835,0.0001484972,0.00006390071,0.00007979992,0.00008333271,0.0007307559,0.008079917,0.0002049652,0.0000221161],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001115736,"about_ca_system_score_gemma":0.00002942614,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001154109,"about_ca_topic_score_gemma":0.00002228778,"domain_scores_codex":[0.9983534,0.00006056784,0.0003720436,0.000616763,0.0002564738,0.0003407137],"domain_scores_gemma":[0.9963306,0.0001035308,0.000404521,0.003032229,0.00004906328,0.00008005306],"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":[0.00001863972,0.0001644901,0.01544347,0.0001963712,0.00005473823,0.0002010899,0.001332895,0.006510367,0.002545555,0.01213146,0.001681172,0.9597198],"study_design_scores_gemma":[0.0002970243,0.00006661699,0.03695001,0.00007110064,0.000004778619,0.00004044029,0.00001091263,0.9587511,0.00007717959,0.0009599895,0.002603644,0.0001671811],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06503548,0.00004810786,0.9041577,0.001487837,0.001709902,0.0002255591,0.00001378207,0.0002457188,0.02707593],"genre_scores_gemma":[0.8879861,0.000004510857,0.1115023,0.0002544708,0.0002194122,8.607558e-7,0.00000359146,0.00001238531,0.0000163408],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9595526,"threshold_uncertainty_score":0.9999425,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09533847730182693,"score_gpt":0.3114753651176342,"score_spread":0.2161368878158073,"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."}}