{"id":"W3205527824","doi":"10.1002/sim.9225","title":"Bayesian consensus clustering for multivariate longitudinal data","year":2021,"lang":"en","type":"article","venue":"Statistics in Medicine","topic":"Liver Disease Diagnosis and Treatment","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Ontario; University of Toronto; Queen's University","funders":"","keywords":"Cluster analysis; Multivariate statistics; Computer science; Data mining; Fuzzy clustering; Bayesian probability; CURE data clustering algorithm; Correlation clustering; Consensus clustering; Clustering high-dimensional data; Artificial intelligence; 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":[0.01884421,0.001527491,0.002951049,0.003175975,0.001429759,0.00183185,0.004334168,0.002696362,0.00327571],"category_scores_gemma":[0.04173208,0.001336348,0.002427616,0.002740071,0.002337333,0.002682628,0.002399975,0.003526403,0.001147454],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003248726,"about_ca_system_score_gemma":0.002990596,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02021977,"about_ca_topic_score_gemma":0.01531462,"domain_scores_codex":[0.9927695,0.00429015,0.0003280483,0.001540384,0.0007750028,0.0002968461],"domain_scores_gemma":[0.9757474,0.01728313,0.0021097,0.001711478,0.002666842,0.0004814646],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001441038,0.00004425848,0.002700534,0.0001626551,0.0002252051,0.0001134558,0.0002327304,0.8903609,0.0004779364,0.07265988,0.002196024,0.03068238],"study_design_scores_gemma":[0.00001209457,0.00001478488,0.0003063686,0.00001550416,0.00001353161,0.00001484123,0.00001953341,0.9661543,0.0001137021,0.03265801,0.0006595241,0.00001780669],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005934862,0.000351735,0.9923984,0.0003294526,0.00004636255,0.00008998275,0.0002228947,0.0002197081,0.0004065279],"genre_scores_gemma":[0.3991307,0.001631291,0.5869797,0.000558534,0.0003534116,0.001294589,0.003170805,0.0004163563,0.006464632],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02021977,"threshold_uncertainty_score":0.09965885,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09591034766605583,"score_gpt":0.3992369993620657,"score_spread":0.3033266516960099,"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."}}