{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01905028,0.0007421449,0.001770847,0.002550272,0.001222215,0.002787756,0.002695357,0.00171323,0.003750399],"category_scores_gemma":[0.07638859,0.0008417095,0.001357866,0.002863046,0.0045687,0.005035932,0.003565455,0.003063951,0.0006278816],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002388825,"about_ca_system_score_gemma":0.002174785,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003219067,"about_ca_topic_score_gemma":0.002872344,"domain_scores_codex":[0.9864688,0.009637178,0.0004797626,0.001490752,0.001573588,0.0003498993],"domain_scores_gemma":[0.9423597,0.0490652,0.002351374,0.00346044,0.002121944,0.0006413654],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001424742,0.00007549566,0.006111394,0.0002569892,0.0001483245,0.0003301571,0.0008462465,0.1685553,0.0006870698,0.7475073,0.002721333,0.07261787],"study_design_scores_gemma":[0.00001788791,0.00001358141,0.0006439534,0.00005563579,0.00001853663,0.0001487632,0.0000990988,0.4459072,0.0004533516,0.550539,0.002074868,0.00002803005],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00617525,0.0002207889,0.9922672,0.0003745343,0.00002824204,0.00004222676,0.0001095263,0.00006971916,0.0007125549],"genre_scores_gemma":[0.3747095,0.0007541826,0.6200325,0.0003094948,0.000202901,0.0006080246,0.0006720921,0.0001195351,0.002591745],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01905028,"threshold_uncertainty_score":0.1007487,"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."}}