{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.06109334,0.002309822,0.002525638,0.002694437,0.0009162451,0.00327409,0.003825132,0.002895038,0.06568772],"category_scores_gemma":[0.220024,0.001805648,0.002994372,0.003562941,0.00122133,0.002207412,0.002701334,0.004082036,0.01768492],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002356097,"about_ca_system_score_gemma":0.00810852,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001729757,"about_ca_topic_score_gemma":0.003453458,"domain_scores_codex":[0.9480053,0.04184568,0.004047276,0.002924173,0.002689667,0.000487923],"domain_scores_gemma":[0.8788955,0.0929418,0.008252466,0.01478663,0.004183896,0.0009396109],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.008088746,0.0004532225,0.00773825,0.01383843,0.002027479,0.0002038571,0.0002144708,0.05135715,0.0007745625,0.0606156,0.5345813,0.320107],"study_design_scores_gemma":[0.02820446,0.001348368,0.005278919,0.003684696,0.001438498,0.0006482449,0.00006193884,0.1357244,0.002334857,0.3059244,0.5150458,0.000305437],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"dataset","genre_scores_codex":[0.003981141,0.003618694,0.6945463,0.00365646,0.0009411352,0.01755679,0.2562164,0.01099188,0.008491136],"genre_scores_gemma":[0.03778061,0.001713856,0.696729,0.002589805,0.0003022021,0.1235984,0.1309642,0.002134573,0.004187408],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.9389067,"threshold_uncertainty_score":0.3230963,"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."}}