{"id":"W2307710747","doi":"","title":"THE NESTED DIRICHLET DISTRIBUTION AND INCOMPLETE CATEGORICAL DATA ANALYSIS","year":2009,"lang":"en","type":"article","venue":"","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Dirichlet distribution; Frequentist inference; Categorical variable; Categorical distribution; Mathematics; Bayes factor; Likelihood function; Conjugate prior; Bayesian probability; Marginal likelihood; Latent Dirichlet allocation; Computer science; Statistics; Prior probability; Bayes' theorem; Bayesian inference; Artificial intelligence; Bayesian linear regression; Maximum likelihood; Topic model","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":[0.0006441653,0.00007981859,0.0001283416,0.00003022919,0.0002268533,0.0002621978,0.0009660184,0.00003364676,0.000001934246],"category_scores_gemma":[0.00005164724,0.00004516347,0.00003160503,0.0008286588,0.00003174101,0.0002813214,0.0003210359,0.0000794226,0.000002685947],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001153875,"about_ca_system_score_gemma":0.00001602676,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000039211,"about_ca_topic_score_gemma":0.00002734504,"domain_scores_codex":[0.9990607,0.0001277238,0.0001432177,0.0003491942,0.0001425207,0.0001766698],"domain_scores_gemma":[0.998583,0.0001491296,0.0000388475,0.001115602,0.0000347453,0.00007865461],"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":[0.000001864314,0.00001407979,0.0001691429,4.496047e-7,0.00003345597,0.000003410195,0.00002593073,0.000002637908,0.00003563828,0.6692755,0.003012476,0.3274254],"study_design_scores_gemma":[0.0001252517,0.00004122994,0.05683057,7.641343e-7,0.00009584223,0.00001420517,0.000003678966,0.7657591,0.00003791262,0.1574633,0.01947805,0.0001502085],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0003749877,0.000179023,0.9911716,0.007245025,0.00004235227,0.00005446902,0.000007697108,0.00006532497,0.0008595158],"genre_scores_gemma":[0.7562049,0.00006175629,0.2428149,0.0005925286,0.00004227036,0.000001388698,0.00007702491,0.000001668256,0.0002035018],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7657564,"threshold_uncertainty_score":0.252838,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03312163371153608,"score_gpt":0.3022740310791047,"score_spread":0.2691523973675686,"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."}}