{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.09806287,0.0004027556,0.002573712,0.0002557334,0.0004554151,0.0001463565,0.001321899,0.0004903388,0.0001195675],"category_scores_gemma":[0.5727199,0.0003355099,0.0005965051,0.0009414696,0.001279618,0.0002543514,0.001093892,0.0008241123,0.000150346],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003589784,"about_ca_system_score_gemma":0.0004037125,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000951291,"about_ca_topic_score_gemma":0.000002905931,"domain_scores_codex":[0.9516116,0.0405378,0.00611735,0.0008232159,0.0004416595,0.0004683726],"domain_scores_gemma":[0.443459,0.5508902,0.001729901,0.003100486,0.0003043371,0.0005161232],"domain_codex":null,"domain_gemma":"methods","domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.01077055,0.006162103,0.001038242,0.0002270538,0.002789726,0.0001185169,0.001269303,0.000001630665,0.003242146,0.263203,0.2110748,0.5001029],"study_design_scores_gemma":[0.01445812,0.0008388478,0.0004431704,0.0003426693,0.0003082078,0.000005781008,0.0004896415,0.01300158,0.0002175328,0.9646258,0.004752405,0.000516282],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01354901,0.002099188,0.937808,0.01774598,0.002065737,0.01168508,0.0007121239,0.002398033,0.01193688],"genre_scores_gemma":[0.3195802,0.0011152,0.6776543,0.0003661299,0.0002773965,0.000476803,0.00003412886,0.00008420034,0.0004116445],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7014228,"threshold_uncertainty_score":0.9999097,"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."}}