{"id":"W2979735657","doi":"10.1109/fuzz-ieee.2019.8858972","title":"Evidential clustering for categorical data","year":2019,"lang":"en","type":"preprint","venue":"","topic":"Advanced Clustering Algorithms Research","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Categorical variable; Cluster analysis; Outlier; Data mining; Computer science; Partition (number theory); Fuzzy clustering; Artificial intelligence; Pattern recognition (psychology); Fuzzy logic; Mathematics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00434071,0.0006236967,0.0009589868,0.002469212,0.0009620305,0.002368398,0.0015645,0.001303868,0.001577582],"category_scores_gemma":[0.01515178,0.0003985192,0.001193727,0.002380605,0.001882338,0.002628477,0.00210487,0.002530594,0.0005822378],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001348285,"about_ca_system_score_gemma":0.001151777,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009209368,"about_ca_topic_score_gemma":0.001078025,"domain_scores_codex":[0.995702,0.001848806,0.0002953615,0.0008565671,0.00116301,0.0001343753],"domain_scores_gemma":[0.9924545,0.00432037,0.000741669,0.001336796,0.0009715679,0.0001750048],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000106039,0.00005610402,0.001470562,0.0004401997,0.0001671677,0.0001583635,0.0007384542,0.1692029,0.004678462,0.6010789,0.002702361,0.2192005],"study_design_scores_gemma":[0.00001127425,0.00004141487,0.000621051,0.00006025776,0.00002320858,0.0001428158,0.00008703587,0.5088382,0.00204786,0.483043,0.005044242,0.00003953919],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003678419,0.0003057559,0.9950414,0.0001187008,0.00001778568,0.00002110974,0.00007146892,0.00007453353,0.0006707049],"genre_scores_gemma":[0.2138576,0.0006303746,0.7833758,0.0001577711,0.0001257692,0.0001303065,0.0005661646,0.00005890412,0.001097326],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00434071,"threshold_uncertainty_score":0.02295613,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1771003509356381,"score_gpt":0.4150464112990636,"score_spread":0.2379460603634255,"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."}}