{"id":"W2127033147","doi":"10.1109/cidm.2009.4938666","title":"Fuzzy p-mode prototypes: A generalization of frequency-based cluster prototypes for clustering categorical objects","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Clustering Algorithms Research","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Thompson Rivers University","funders":"","keywords":"Fuzzy clustering; Cluster analysis; Categorical variable; Pattern recognition (psychology); FLAME clustering; Fuzzy logic; Generalization; Fuzzy set; Artificial intelligence; Mathematics; Data mining; Computer science; Feature (linguistics); CURE data clustering algorithm; Machine learning","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":[0.0003203317,0.000225041,0.0002892965,0.0002309058,0.0001278076,0.0001037427,0.0008460716,0.0001207649,0.000006207383],"category_scores_gemma":[0.0001340179,0.0001956713,0.0001065737,0.0005894117,0.00004857156,0.0005178457,0.0001265852,0.0001374314,0.000007978972],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001344927,"about_ca_system_score_gemma":0.000256281,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005783532,"about_ca_topic_score_gemma":0.0000358923,"domain_scores_codex":[0.9978957,0.0000834465,0.0004415331,0.0005718893,0.0004775053,0.0005299054],"domain_scores_gemma":[0.9985679,0.0001077235,0.0001359521,0.0006671002,0.0003883917,0.0001329277],"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":[0.0008342315,0.001677884,0.0006675163,0.002063357,0.000130176,0.0000551932,0.00356889,0.4079024,0.154763,0.1900011,0.001088646,0.2372476],"study_design_scores_gemma":[0.00117955,0.0008532956,0.0001833843,0.00004550654,0.000004965582,0.00001014772,0.00001045115,0.9203085,0.0449879,0.03192241,0.0002022793,0.0002916348],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001223093,0.00003042837,0.9920475,0.0009441851,0.0001047613,0.003831142,0.000004602286,0.0002588176,0.001555393],"genre_scores_gemma":[0.4022968,0.000002723576,0.5962121,0.0003650232,0.00008227321,0.0007795805,0.0000111483,0.00001948264,0.00023082],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5124061,"threshold_uncertainty_score":0.7979243,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02177035882438115,"score_gpt":0.3235427786971909,"score_spread":0.3017724198728098,"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."}}