{"id":"W2091793380","doi":"10.1002/wics.102","title":"Bayesian inference: an approach to statistical inference","year":2010,"lang":"en","type":"review","venue":"Wiley Interdisciplinary Reviews Computational Statistics","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Prior probability; Bayes' theorem; Statistical inference; Frequentist inference; Bayesian probability; Inference; Bayes factor; Mathematics; Computer science; Bayesian inference; Artificial intelligence; 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":[0.02086049,0.00157826,0.002753822,0.006709438,0.00090175,0.006242874,0.004205078,0.004615796,0.003750375],"category_scores_gemma":[0.03836905,0.001420973,0.001639391,0.006415354,0.01175518,0.006886754,0.002966393,0.008374342,0.002073698],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004632597,"about_ca_system_score_gemma":0.003618504,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004338461,"about_ca_topic_score_gemma":0.002690863,"domain_scores_codex":[0.9826373,0.01152513,0.000670371,0.001287107,0.003715201,0.0001648241],"domain_scores_gemma":[0.9742277,0.02208328,0.0006997954,0.001123088,0.001651881,0.0002141197],"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":[0.000008964122,0.00001181806,0.0001483529,0.0005181504,0.0001123702,0.00005326159,0.0001435175,0.006615295,0.00009486714,0.9288536,0.00511919,0.05832047],"study_design_scores_gemma":[0.000006883267,0.000004722555,0.00008282698,0.0002213208,0.00001534245,0.0000554211,0.00002187717,0.006362641,0.00005670367,0.9730121,0.02014631,0.00001375983],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.0004108771,0.06278247,0.9165899,0.009001987,0.0006840703,0.00005875445,0.0001248825,0.0001413541,0.01020567],"genre_scores_gemma":[0.107016,0.1697877,0.6974827,0.007165493,0.007227959,0.0007700307,0.0003430105,0.0003747946,0.009832363],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.02086049,"threshold_uncertainty_score":0.1103222,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1451709663558175,"score_gpt":0.485227297478791,"score_spread":0.3400563311229735,"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."}}