{"id":"W4388569182","doi":"10.1016/j.conctc.2023.101229","title":"A promising biomarker adaptive Phase 2/3 design – Explained and expanded","year":2023,"lang":"en","type":"article","venue":"Contemporary Clinical Trials Communications","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Canada Research Chairs; Michael Smith Health Research BC","keywords":"Biomarker; Interim; Population; Phase (matter); Interim analysis; Computer science; Oncology; Statistics; Medicine; Internal medicine; Biology; Mathematics; Clinical trial; Chemistry; Environmental health; Genetics; Geography","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.03691159,0.001143818,0.001356078,0.0006856393,0.0004699248,0.001542881,0.001455206,0.001823894,0.007927352],"category_scores_gemma":[0.03949026,0.00063138,0.002591556,0.0005853086,0.001335725,0.001458599,0.001670404,0.003483378,0.001482258],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007499962,"about_ca_system_score_gemma":0.002776966,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002392416,"about_ca_topic_score_gemma":0.0003476547,"domain_scores_codex":[0.9676384,0.02813218,0.0006197702,0.001411424,0.001862286,0.000336015],"domain_scores_gemma":[0.9795791,0.01429803,0.001269614,0.002548356,0.001692574,0.0006124175],"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":[0.022443,0.001400863,0.004302408,0.001984373,0.001720661,0.0004693177,0.0005862422,0.06079371,0.02042099,0.2401272,0.02540123,0.6203499],"study_design_scores_gemma":[0.01440881,0.03196,0.003325722,0.001093536,0.002114623,0.0009110763,0.0001117785,0.2325735,0.01848423,0.54777,0.1468423,0.0004044978],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01237453,0.002118995,0.9716162,0.004336137,0.001372299,0.002998329,0.00035454,0.0005656714,0.004263224],"genre_scores_gemma":[0.113949,0.001396626,0.8635691,0.006171767,0.0008685974,0.009503346,0.000300128,0.0003026214,0.003938854],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03691159,"threshold_uncertainty_score":0.1952095,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9770189941231097,"score_gpt":0.7283008112332489,"score_spread":0.2487181828898608,"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."}}