{"id":"W7036217496","doi":"","title":"Bayesian Model Selection for Discrete Graphical Models","year":2023,"lang":"en","type":"other","venue":"York University Digital Library (York University)","topic":"Scientific Research and Technology","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"York University","keywords":"Graphical model; Bayes factor; Model selection; Conditional independence; Dirichlet distribution; Prior probability; Posterior probability; Bayes' theorem; Contingency table; Multinomial distribution","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00005129663,0.0003859734,0.00039034,0.002884743,0.000557144,0.0004307635,0.003277755,0.0006204601,0.00005781001],"category_scores_gemma":[0.00001567963,0.0004605136,0.0003851799,0.003925157,0.0003633894,0.003484521,0.001840034,0.0004311814,0.00009036756],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001334875,"about_ca_system_score_gemma":0.0004336444,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000542226,"about_ca_topic_score_gemma":0.0001311101,"domain_scores_codex":[0.9974236,0.00005455304,0.0001356553,0.001204317,0.0004163148,0.0007655654],"domain_scores_gemma":[0.9984808,0.0001226905,0.0001667448,0.0007869748,0.00003953584,0.0004032289],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007732854,0.00006931155,0.0001176639,0.00003731712,0.0001363481,0.0001215294,0.00004946021,0.0007043229,0.000002005657,0.4513983,0.5446022,0.002684286],"study_design_scores_gemma":[0.0006206394,0.0001153188,0.000002773993,0.00007636644,0.00002202633,0.000005466315,0.0001706841,0.2005508,0.00001341822,0.01838432,0.7795193,0.000518845],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.00001917258,0.00002883353,0.5912881,0.0004533857,0.0002140204,0.0004481327,0.0008677167,0.004411009,0.4022695],"genre_scores_gemma":[0.007151194,0.0001330406,0.01503216,0.00003253949,0.00007626067,6.089529e-7,0.0002282273,0.0002851591,0.9770608],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.576256,"threshold_uncertainty_score":0.9997846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01815643423579291,"score_gpt":0.1892684056424449,"score_spread":0.171111971406652,"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."}}