{"id":"W4394255645","doi":"10.6084/m9.figshare.19329384","title":"Bayesian Optimal Phase II Design for Randomized Clinical Trials","year":2022,"lang":"en","type":"dataset","venue":"Figshare","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Bayesian probability; Phase (matter); Randomized controlled trial; Computer science; Statistics; Mathematics; Artificial intelligence; Medicine; Internal medicine; Chemistry","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow","research_integrity","insufficient_payload"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.08582973,0.000852808,0.009323575,0.0002057755,0.0004380925,0.0001519065,0.001708248,0.001470093,0.9376826],"category_scores_gemma":[0.9772646,0.0006854622,0.003742657,0.0002512299,0.00009842367,0.00006290546,0.00101355,0.001919913,0.0004306429],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001037803,"about_ca_system_score_gemma":0.0007037885,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002346691,"about_ca_topic_score_gemma":7.693783e-7,"domain_scores_codex":[0.9446548,0.04433847,0.007863729,0.001389679,0.0009839589,0.0007693379],"domain_scores_gemma":[0.09870739,0.8935135,0.004925427,0.001939054,0.0003629938,0.0005516166],"domain_codex":null,"domain_gemma":"methods","domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.06332058,0.001252651,7.815763e-10,0.001038695,0.0008446607,0.00005506174,0.000006771027,0.000005235176,1.091043e-7,0.000108682,0.9267225,0.006645012],"study_design_scores_gemma":[0.1743582,0.001237435,3.002896e-9,0.0008365396,0.001621214,0.000004556863,0.000004544984,0.0007051916,0.000007199527,0.1149959,0.7056711,0.0005581484],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[1.251046e-8,0.0001282487,0.06260476,0.0001191656,0.001822922,0.01226705,0.9228677,0.0001502815,0.00003981953],"genre_scores_gemma":[1.55162e-8,0.00003237939,0.3869062,0.0003144587,0.001835436,0.010995,0.5996153,0.00009249358,0.0002087061],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9372519,"threshold_uncertainty_score":0.9998262,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8556465411061355,"score_gpt":0.6767526664510932,"score_spread":0.1788938746550423,"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."}}