{"id":"W2093310116","doi":"10.1111/j.1744-7976.2001.tb00308.x","title":"Bayesian Inference and Posterior Simulators","year":2001,"lang":"fr","type":"article","venue":"Canadian Journal of Agricultural Economics/Revue canadienne d agroeconomie","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bayesian probability; Bayesian inference; Presentation (obstetrics); Computer science; Inference; Operations research; Library science; Artificial intelligence; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01545892,0.001106909,0.002140346,0.002625411,0.0009347826,0.003638734,0.002385265,0.00329928,0.008575494],"category_scores_gemma":[0.08377822,0.001169177,0.001806549,0.001870086,0.004130928,0.00519172,0.002856975,0.003787679,0.001182039],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002489199,"about_ca_system_score_gemma":0.002467868,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004760921,"about_ca_topic_score_gemma":0.003591565,"domain_scores_codex":[0.9910786,0.006592099,0.0002971635,0.0006994437,0.001014041,0.0003187479],"domain_scores_gemma":[0.9521806,0.04319464,0.001114828,0.001773279,0.001318066,0.0004185999],"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":[0.00003674477,0.0000231457,0.0005415974,0.0000781265,0.00005192479,0.00004435775,0.0001372613,0.1725973,0.00009512671,0.8109568,0.0009464642,0.01449115],"study_design_scores_gemma":[0.00002294597,0.00001409798,0.0001115804,0.0000454972,0.00001383886,0.00002189769,0.00002238463,0.3427567,0.0000981475,0.6546963,0.002179603,0.00001679598],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004115848,0.0006345542,0.9877129,0.0009634462,0.00006744343,0.00006049178,0.0001081031,0.0001015925,0.006235741],"genre_scores_gemma":[0.4012867,0.003902311,0.5777305,0.0007359628,0.0004653025,0.001155745,0.0006875289,0.0001961314,0.01383977],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01545892,"threshold_uncertainty_score":0.08175558,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07104408598911092,"score_gpt":0.2828379342917801,"score_spread":0.2117938483026692,"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."}}