{"id":"W2992636254","doi":"10.1002/sim.8414","title":"Optimizing interim analysis timing for Bayesian adaptive commensurate designs","year":2019,"lang":"en","type":"article","venue":"Statistics in Medicine","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Xenon Pharmaceuticals (Canada)","funders":"Sanofi","keywords":"Interim; Bayesian probability; Interim analysis; Computer science; Adaptive design; Econometrics; Statistics; Artificial intelligence; Mathematics; Medicine; Clinical trial; Internal medicine","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.006541156,0.0002325876,0.0009122474,0.0009215321,0.00008528848,0.0000701718,0.0006179069,0.00007901041,0.001760948],"category_scores_gemma":[0.004335207,0.0001763916,0.00009401648,0.001695691,0.0002201463,0.0001556902,0.0001184448,0.0002144667,0.00006585135],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000147735,"about_ca_system_score_gemma":0.00004974074,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000106111,"about_ca_topic_score_gemma":0.00005645369,"domain_scores_codex":[0.9963626,0.0005979744,0.001052981,0.0006378673,0.0009445792,0.000404049],"domain_scores_gemma":[0.9894605,0.009114387,0.0003575578,0.000580201,0.0003337502,0.0001535623],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004912392,0.0006406633,0.04996961,0.000176837,0.002707511,0.0004038732,0.06291028,0.09809724,0.1205921,0.2765997,0.08787841,0.2951113],"study_design_scores_gemma":[0.001850471,0.001389678,0.001906518,0.00008957319,0.0002319694,0.000003825767,0.01034652,0.941,0.001559343,0.04028432,0.0009794036,0.0003583249],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002559738,0.0001387708,0.9904547,0.0003439042,0.0005359823,0.0005822962,0.0001297451,0.00002125915,0.005233659],"genre_scores_gemma":[0.3593259,0.000006831256,0.6393849,0.0004034993,0.00004298544,0.00002689098,0.00002690749,0.00001764106,0.0007644379],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8429028,"threshold_uncertainty_score":0.9991516,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2877791635705335,"score_gpt":0.511439466930051,"score_spread":0.2236603033595175,"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."}}