{"id":"W4389988630","doi":"10.1109/ictai59109.2023.00078","title":"Unsupervised Learning of Dirichlet Compound Negative Multinomial Mixture Model using Minorization-Maximization Approach","year":2023,"lang":"en","type":"article","venue":"","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Multinomial distribution; Computer science; Maximization; Mixture model; Latent Dirichlet allocation; Dirichlet distribution; Artificial intelligence; Statistics; Mathematical optimization; Topic model; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003902868,0.0001704589,0.0002558887,0.0002194686,0.0001803023,0.00008310164,0.0004423526,0.0001187367,0.000005450388],"category_scores_gemma":[0.0001066073,0.0001528958,0.00007782668,0.00118951,0.00004802672,0.0004432025,0.0002066575,0.0001650862,0.000003831753],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003150425,"about_ca_system_score_gemma":0.00009253035,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004633194,"about_ca_topic_score_gemma":0.00000126484,"domain_scores_codex":[0.9985482,0.0002072476,0.0003054844,0.0004144501,0.0002682251,0.0002564403],"domain_scores_gemma":[0.9991258,0.0001544769,0.0001483604,0.0003065236,0.0001895296,0.0000752816],"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":[0.00001176158,0.00006951159,0.000290616,0.00005093994,0.00002917047,0.000002582848,0.004122558,0.9054871,0.01398603,0.0613884,0.0002034365,0.01435794],"study_design_scores_gemma":[0.0003952422,0.00001883028,0.0001372774,0.00001220057,0.00001103963,0.000002350608,0.00006610309,0.9837421,0.002952786,0.01247301,0.00001438591,0.0001746442],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02314769,0.00001601862,0.9728114,0.00009274857,0.000108203,0.0002227877,0.00000300069,0.000244525,0.003353633],"genre_scores_gemma":[0.3382649,0.000005781827,0.661054,0.00006343128,0.00003701694,0.000004833717,0.00001769616,0.00001281126,0.0005395641],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3151172,"threshold_uncertainty_score":0.6234911,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0395876110850217,"score_gpt":0.2798042658183521,"score_spread":0.2402166547333304,"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."}}