{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002363452,0.0001401316,0.0003866271,0.0000670247,0.00004922811,0.000008443128,0.00008676588,0.00004154454,0.0003447457],"category_scores_gemma":[0.001361906,0.0001137053,0.00002090954,0.0001240893,0.0001008934,0.00001922089,0.0001032346,0.0001014634,0.000007282991],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007829528,"about_ca_system_score_gemma":0.0001816487,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002235225,"about_ca_topic_score_gemma":0.0004482601,"domain_scores_codex":[0.9987581,0.00003681094,0.0003281911,0.0004122862,0.000224989,0.0002396124],"domain_scores_gemma":[0.9983355,0.000675556,0.00006117724,0.0005856068,0.0001708546,0.0001713136],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002211721,0.00387341,0.5645339,0.003651578,0.002071617,0.029554,0.002173224,0.0001540057,0.001744048,0.03118337,0.2424985,0.1163506],"study_design_scores_gemma":[0.03389185,0.001265099,0.7558423,0.002548053,0.002496426,0.0003961675,0.001445066,0.1778679,0.0003919582,0.007225646,0.01610055,0.0005290644],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02569059,0.006178168,0.9267725,0.02101001,0.002305637,0.00271443,0.009794326,0.0001230323,0.005411296],"genre_scores_gemma":[0.8134419,0.0002973425,0.1799679,0.0008239534,0.0004371029,0.00006304692,0.004472421,0.0000346151,0.0004617294],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7877513,"threshold_uncertainty_score":0.4636766,"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."}}