{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01400356,0.0007782599,0.002374697,0.004456818,0.0003534502,0.001939913,0.001675345,0.002333378,0.004115353],"category_scores_gemma":[0.0255635,0.0005823153,0.001605002,0.0053778,0.001659666,0.002189264,0.001174349,0.002995202,0.0009418089],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001997157,"about_ca_system_score_gemma":0.00439635,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001805886,"about_ca_topic_score_gemma":0.001925445,"domain_scores_codex":[0.9894397,0.007057475,0.0008652505,0.0005542321,0.001964927,0.0001183759],"domain_scores_gemma":[0.9758084,0.02131545,0.001048769,0.0004464594,0.001216275,0.0001646101],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001343706,0.00007675828,0.000595845,0.02965943,0.0008036474,0.0001836549,0.0002081006,0.006504139,0.0003407842,0.07178231,0.01493759,0.8747734],"study_design_scores_gemma":[0.0003144545,0.0004387692,0.003485697,0.03951368,0.001585947,0.002526876,0.0002028338,0.01141808,0.001325583,0.3088874,0.6301188,0.0001818232],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0003339015,0.9647008,0.02699846,0.002876435,0.000352827,0.0001197452,0.00007017804,0.00004295195,0.004504624],"genre_scores_gemma":[0.01416704,0.9577395,0.02472179,0.001327247,0.0007839159,0.0003193978,0.00008931847,0.00002078473,0.000830903],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.01400356,"threshold_uncertainty_score":0.07405877,"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."}}