{"id":"W3081849395","doi":"10.1002/pst.2067","title":"A stochastically curtailed two‐arm randomised phase<scp>II</scp>trial design for binary outcomes","year":2020,"lang":"en","type":"article","venue":"Pharmaceutical Statistics","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Medical Research Council; Medical Research Council Canada; Cancer Research UK","keywords":"Interim; Interim analysis; Research design; Early stopping; Sample size determination; Outcome (game theory); Clinical study design; Null hypothesis; Randomized controlled trial; Computer science; Statistics; Medicine; Mathematics; Clinical trial; Surgery; Machine learning; Internal medicine","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.05911991,0.001369387,0.002926586,0.001175858,0.0007750357,0.001778245,0.002029651,0.003734217,0.01578806],"category_scores_gemma":[0.0924496,0.0005824002,0.00300587,0.001302084,0.002382058,0.001678175,0.001631183,0.00423995,0.003232082],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001042986,"about_ca_system_score_gemma":0.004967022,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002062509,"about_ca_topic_score_gemma":0.0003685362,"domain_scores_codex":[0.9187651,0.06807788,0.004208633,0.002886559,0.005488507,0.0005733541],"domain_scores_gemma":[0.9441649,0.03892211,0.005974454,0.006505595,0.003406122,0.001026801],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0350894,0.002140113,0.002748968,0.02342133,0.002474804,0.0003843598,0.0006895547,0.02293896,0.01008861,0.3814926,0.03262688,0.4859044],"study_design_scores_gemma":[0.09849352,0.08377174,0.005227942,0.008253669,0.003979904,0.001783491,0.000244915,0.1462693,0.01775889,0.3566,0.276814,0.0008025949],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007480949,0.002159482,0.9124393,0.002249593,0.002712216,0.06460018,0.0009390882,0.0006905325,0.006728589],"genre_scores_gemma":[0.08755428,0.001788205,0.704229,0.004600532,0.0008652895,0.1955128,0.0005938801,0.0001898102,0.004666238],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9408801,"threshold_uncertainty_score":0.3126597,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6908497330030037,"score_gpt":0.6098577142060511,"score_spread":0.08099201879695261,"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."}}