{"id":"W1978559040","doi":"10.1007/s00500-008-0334-8","title":"Fuzzy relational clustering based on comparing two proximity matrices with utilization of particle swarm optimization","year":2008,"lang":"en","type":"article","venue":"Soft Computing","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Thompson Rivers University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Fuzzy clustering; Cluster analysis; Data mining; FLAME clustering; Feature vector; Relational database; Feature (linguistics); Pattern recognition (psychology); Basis (linear algebra); Mathematics; Artificial intelligence; Fuzzy logic; Computer science; CURE data clustering algorithm","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002020928,0.0001890546,0.0003610065,0.0003359444,0.0004823936,0.0001362631,0.0004084671,0.00005664611,0.00005718894],"category_scores_gemma":[0.001566515,0.0001527771,0.00007617461,0.001298455,0.000112658,0.0004796454,0.0001848805,0.0001561232,0.00002687032],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000663648,"about_ca_system_score_gemma":0.00009766546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002328067,"about_ca_topic_score_gemma":0.00002166089,"domain_scores_codex":[0.996151,0.0002815423,0.0009800652,0.0005612567,0.001738692,0.0002873868],"domain_scores_gemma":[0.996066,0.002052521,0.0007176145,0.0004799879,0.0005896211,0.00009422485],"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":[0.0001198099,0.00007233123,0.1350846,0.000008170278,0.000004966451,0.000005710669,0.0004746101,0.8591115,0.00009373285,0.0003764704,0.00002865523,0.004619357],"study_design_scores_gemma":[0.001109413,0.00006897539,0.04176274,0.0001365288,0.000007742916,0.00001573501,0.0001186987,0.9558468,0.0005054592,0.0002359658,0.00002759877,0.0001643858],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4407425,0.00001659265,0.5579145,0.00005167902,0.0001195,0.0001603502,0.00000157069,0.00006751058,0.0009258615],"genre_scores_gemma":[0.8708424,7.656114e-7,0.1289418,0.00008112143,0.00007463553,0.000002613102,0.000007176335,0.00001925094,0.00003023013],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4300999,"threshold_uncertainty_score":0.6230069,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2486164222726114,"score_gpt":0.3945126189860804,"score_spread":0.1458961967134689,"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."}}