{"id":"W76294416","doi":"","title":"Influence of clustering pre-processing on genetically generated fuzzy knowledge bases","year":2005,"lang":"en","type":"article","venue":"PolyPublie (École Polytechnique de Montréal)","topic":"Evolutionary Algorithms and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Cluster analysis; Computer science; Fuzzy clustering; Data mining; Outlier; CURE data clustering algorithm; Data stream clustering; Artificial intelligence; Correlation clustering; Canopy clustering algorithm; Noise (video); Fuzzy logic; Machine learning; Process (computing); Pattern recognition (psychology)","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":[],"consensus_categories":[],"category_scores_codex":[0.0003221832,0.0002446106,0.0002396815,0.0002777117,0.0002736804,0.0001244374,0.001008741,0.0001446952,0.000005907792],"category_scores_gemma":[0.00006651917,0.0002445536,0.00008680575,0.0008169385,0.00009646724,0.0005316134,0.0003556735,0.0002418692,0.00002283857],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002063279,"about_ca_system_score_gemma":0.00028242,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004451957,"about_ca_topic_score_gemma":0.0005558312,"domain_scores_codex":[0.9981875,0.00007614723,0.0004904623,0.0004955289,0.0002809387,0.0004693769],"domain_scores_gemma":[0.9984099,0.00009305318,0.0001917378,0.0008460536,0.000245135,0.0002141096],"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":[0.00002649192,0.0006979142,0.0017976,0.00005159669,0.00002146951,0.000007312527,0.0004472483,0.6488139,0.05405463,0.0721641,0.0006982103,0.2212195],"study_design_scores_gemma":[0.0002241698,0.000117649,0.04610801,0.00007807606,0.000008301477,0.00003755054,0.000006841477,0.9239598,0.02599324,0.001119942,0.002074039,0.0002723786],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2783094,0.0008704802,0.7176136,0.001829159,0.00001909951,0.0002806618,0.000009797888,0.0003961817,0.0006716156],"genre_scores_gemma":[0.6734179,0.00006587706,0.3252828,0.0006996047,0.00009995792,0.0001829378,0.000004275923,0.0000184361,0.0002282548],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.3951085,"threshold_uncertainty_score":0.9972607,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01094977893640601,"score_gpt":0.2472803937707942,"score_spread":0.2363306148343882,"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."}}