{"id":"W2053972562","doi":"10.1080/00949650903409999","title":"Evaluation of algorithms for generating Dirichlet random vectors","year":2010,"lang":"en","type":"article","venue":"Journal of Statistical Computation and Simulation","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Mathematics; Algorithm; Dirichlet distribution; Sensitivity (control systems); Random number generation; Transformation (genetics); Goodness of fit; Statistics","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":[0.01506288,0.001610996,0.001711062,0.003588336,0.001349928,0.002629428,0.003796926,0.003080971,0.005240186],"category_scores_gemma":[0.07359656,0.0007505042,0.001024407,0.002893151,0.001069231,0.004405779,0.002286171,0.001758792,0.001593744],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002862144,"about_ca_system_score_gemma":0.002541187,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004222333,"about_ca_topic_score_gemma":0.004059732,"domain_scores_codex":[0.9885825,0.00682984,0.0007038733,0.001143106,0.002348495,0.0003922019],"domain_scores_gemma":[0.9447441,0.04538871,0.001016349,0.003343655,0.004939223,0.0005679023],"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":[0.000934231,0.0003439086,0.003168649,0.0004478902,0.000230517,0.00008447466,0.0003183925,0.4755164,0.00183563,0.06106326,0.00496062,0.4510959],"study_design_scores_gemma":[0.0001268538,0.00006383906,0.0002505304,0.00003906928,0.0000321198,0.00008319952,0.00006104144,0.9746103,0.003396472,0.01932407,0.001983803,0.00002869469],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0192893,0.0009332874,0.9750572,0.000176389,0.0001030178,0.000272438,0.0001691899,0.001894464,0.002104732],"genre_scores_gemma":[0.09846124,0.0006206438,0.8982333,0.0000890368,0.00005263567,0.0004998829,0.0007336095,0.0004892256,0.0008204692],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01506288,"threshold_uncertainty_score":0.07966107,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05694458435473418,"score_gpt":0.3926531750792768,"score_spread":0.3357085907245426,"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."}}