{"id":"W2132981975","doi":"10.14740/wjon842e","title":"Application of Bayesian Approach in Cancer Clinical Trial","year":2014,"lang":"en","type":"review","venue":"World Journal of Oncology","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Bayesian probability; Medicine; Bayesian inference; Bayesian experimental design; Statement (logic); Clinical trial; Bayesian statistics; Inference; Machine learning; Medical physics; Artificial intelligence; Computer science; Internal medicine","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.02599716,0.0003372396,0.008988425,0.0005819139,0.00001825835,0.000008843826,0.0008770812,0.0009195554,0.0001540065],"category_scores_gemma":[0.05001528,0.000239548,0.001440625,0.0006470135,0.0003365223,0.00003012373,0.0001178543,0.002225456,0.000006785907],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003728535,"about_ca_system_score_gemma":0.001321596,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000762998,"about_ca_topic_score_gemma":0.00003875896,"domain_scores_codex":[0.9808457,0.008713805,0.009308519,0.0003816626,0.0004469104,0.0003033578],"domain_scores_gemma":[0.8865678,0.1032002,0.009304579,0.0004906582,0.000244587,0.0001922043],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002062416,0.001225678,0.00001708066,0.005052182,0.0002610571,0.00001186321,0.00001029877,9.691075e-7,3.29942e-8,0.01886266,0.002078539,0.9704172],"study_design_scores_gemma":[0.01355802,0.001329184,0.000004938862,0.00321385,0.001685596,0.00003559459,0.000003450985,0.00003664816,8.928605e-8,0.1484749,0.831477,0.0001807317],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000002394775,0.7412764,0.2481756,0.0001465912,0.003691733,0.002064428,0.0000304557,0.000009970695,0.004602388],"genre_scores_gemma":[0.000007423349,0.5989381,0.3983107,0.00004104966,0.002496312,0.00009105912,0.000001036426,0.0000392441,0.00007509263],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9702365,"threshold_uncertainty_score":0.9768482,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7526338008122788,"score_gpt":0.6983310240118346,"score_spread":0.05430277680044426,"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."}}