{"id":"W4391944190","doi":"10.1214/23-sts907","title":"Past, Present and Future of Software for Bayesian Inference","year":2024,"lang":"en","type":"article","venue":"Statistical Science","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Office of Naval Research; Javna Agencija za Raziskovalno Dejavnost RS","keywords":"Computer science; Inference; Bayesian inference; Bayesian probability; Software; Artificial intelligence; Machine learning; Econometrics; Data science; Data mining; Mathematics; Programming language","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":[0.0004848568,0.000108021,0.0001346425,0.00009343469,0.0001418591,0.0003326478,0.0006543035,0.00003921313,0.00001444524],"category_scores_gemma":[0.0001371042,0.00008417116,0.00001994901,0.0006971183,0.0005463273,0.0004429066,0.0002233064,0.0001051837,0.000005004834],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002057708,"about_ca_system_score_gemma":0.0003329809,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001636257,"about_ca_topic_score_gemma":0.000001342629,"domain_scores_codex":[0.9985223,0.00002008501,0.0001976377,0.0005470263,0.0003792245,0.0003337574],"domain_scores_gemma":[0.9987407,0.0005710237,0.00002732275,0.0002675275,0.0001889802,0.0002044476],"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":[0.000001715115,0.000009431608,0.00004544033,0.00006141536,0.000001844511,0.000003340921,0.0001754798,0.00001119853,0.0002251156,0.6414068,0.0006327028,0.3574255],"study_design_scores_gemma":[0.00008904705,0.0002163621,0.001892201,0.00007565884,0.000008175109,0.00001252847,0.00002512887,0.6458101,0.0005961928,0.3423986,0.00867708,0.0001989424],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0002616813,0.0003677311,0.9962038,0.002173763,0.000368905,0.0001315731,0.00005620152,0.0001093118,0.0003269863],"genre_scores_gemma":[0.5725663,0.00002251412,0.4270901,0.00005807304,0.000205328,0.00001582896,0.000001548867,0.000004058037,0.00003620674],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6457989,"threshold_uncertainty_score":0.34324,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02079020362936505,"score_gpt":0.3162545814338298,"score_spread":0.2954643778044647,"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."}}