{"id":"W4386636102","doi":"10.1007/s44199-023-00062-8","title":"Smoothed Dirichlet Distribution","year":2023,"lang":"en","type":"article","venue":"Journal of Statistical Theory and Applications","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; University of Winnipeg","funders":"","keywords":"Dirichlet distribution; Multinomial distribution; Mathematics; Generalized Dirichlet distribution; Categorical distribution; Concentration parameter; Distribution (mathematics); Marginal distribution; Applied mathematics; Joint probability distribution; Probability distribution; Statistics; Econometrics; Dirichlet's principle; Mathematical analysis; Random variable; Inverse-chi-squared distribution; Distribution fitting","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":[0.001195191,0.00005166211,0.0001090892,0.00004047477,0.0001014962,0.00005111117,0.0002004014,0.00002780468,0.00000984712],"category_scores_gemma":[0.0001309315,0.00003857126,0.00002728085,0.0002783621,0.00006810124,0.000111769,0.00004852574,0.0001090172,0.00001499559],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000830109,"about_ca_system_score_gemma":0.00002340382,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":1.972377e-7,"about_ca_topic_score_gemma":4.186727e-8,"domain_scores_codex":[0.9993472,0.0001448542,0.0002001236,0.00009516316,0.0001086511,0.0001039871],"domain_scores_gemma":[0.9987487,0.0008600309,0.00009109933,0.0001296318,0.00006767931,0.0001028277],"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":[0.000005555682,0.00001539593,0.00000579222,0.000004148998,0.000006099205,0.000003996862,0.00003100259,0.000001706808,0.0001557776,0.8063448,0.001106207,0.1923195],"study_design_scores_gemma":[0.0001067304,0.00003365983,0.001559298,0.000005981784,0.00001086757,0.00003626759,0.00001108114,0.001281766,0.0000963172,0.9759026,0.02090834,0.00004711122],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0002920527,0.00007814373,0.9982161,0.0006465486,0.00004005067,0.00006206055,0.00004387159,0.00002689702,0.0005943121],"genre_scores_gemma":[0.4597492,0.000295613,0.5389546,0.0003400384,0.0002667203,0.000030314,0.00001866141,0.000009047503,0.0003358133],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4594572,"threshold_uncertainty_score":0.157289,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0133502267024331,"score_gpt":0.3074035470391437,"score_spread":0.2940533203367107,"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."}}