{"id":"W4409589724","doi":"10.1007/978-3-031-85870-3_2","title":"A Multivariate Functional Data Clustering Method Using Parsimonious Cluster Weighted Models","year":2025,"lang":"en","type":"book-chapter","venue":"Studies in classification, data analysis, and knowledge organization","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta; MacEwan University","funders":"","keywords":"Multivariate statistics; Cluster analysis; Cluster (spacecraft); Computer science; Data mining; Statistics; Artificial intelligence; Mathematics","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":[0.003322924,0.001315688,0.001537584,0.003274406,0.001703854,0.001863593,0.003846929,0.001589596,0.005538292],"category_scores_gemma":[0.008613519,0.001041776,0.002522485,0.00458058,0.001234921,0.002775791,0.002480498,0.002801317,0.002388019],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009682046,"about_ca_system_score_gemma":0.001658983,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004926616,"about_ca_topic_score_gemma":0.006741467,"domain_scores_codex":[0.9981123,0.0006731185,0.0001062144,0.0004041637,0.0006255776,0.00007847507],"domain_scores_gemma":[0.9975417,0.001042717,0.0001418232,0.0004635067,0.0007320542,0.00007826956],"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":[0.0001756654,0.0001316213,0.001249325,0.0003463586,0.0003848315,0.0001085087,0.0006739664,0.09023528,0.008628831,0.1423379,0.01228937,0.7434384],"study_design_scores_gemma":[0.00002390833,0.00003617343,0.0008902814,0.00004507209,0.000105228,0.0002209497,0.0001103696,0.8584021,0.003661796,0.1247379,0.01169388,0.00007226422],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0005898265,0.00002693616,0.9988322,0.00003415464,0.00001180535,0.00001800537,0.00004034161,0.0002127138,0.0002339756],"genre_scores_gemma":[0.008686967,0.00005125381,0.9895859,0.00003478652,0.00001658787,0.000118099,0.0002353457,0.0002708192,0.001000214],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005538292,"threshold_uncertainty_score":0.01852739,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2340206200370151,"score_gpt":0.4014019355760586,"score_spread":0.1673813155390435,"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."}}