{"id":"W2134647083","doi":"10.1093/biostatistics/kxn037","title":"Statistical monitoring of clinical trials with multivariate response and/or multiple arms: a flexible approach","year":2008,"lang":"en","type":"article","venue":"Biostatistics","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"National Institute of Allergy and Infectious Diseases; ACT Government","keywords":"Interim; Multivariate statistics; Clinical trial; Robustness (evolution); Computer science; Randomized controlled trial; Interim analysis; Multivariate analysis; Statistics; Medicine; Mathematics; Machine learning; 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":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.02340293,0.0004451883,0.002830984,0.0001472932,0.0001700645,0.00003651802,0.0003137706,0.0003916028,0.0001052451],"category_scores_gemma":[0.629181,0.0002950654,0.0001692872,0.0003546556,0.00135179,0.00007553144,0.0001672423,0.000620198,0.00001130771],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004106017,"about_ca_system_score_gemma":0.0004451608,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000424498,"about_ca_topic_score_gemma":0.000001736209,"domain_scores_codex":[0.9847631,0.008692994,0.004287093,0.0008294447,0.0008563355,0.0005710188],"domain_scores_gemma":[0.6825101,0.315048,0.001146631,0.0005794104,0.0003119875,0.000403943],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.2461676,0.009590223,0.3115653,0.003703408,0.00308989,0.002122219,0.004679816,0.00005139089,0.003339944,0.2734306,0.01148663,0.1307731],"study_design_scores_gemma":[0.04035088,0.01021797,0.5279213,0.001216029,0.00226572,0.0005399532,0.002369328,0.01729994,0.006714161,0.3870822,0.001418152,0.002604374],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.09901484,0.00004561792,0.8968894,0.00006602363,0.0005710262,0.001090738,0.002035609,0.0001421296,0.0001445635],"genre_scores_gemma":[0.2086388,0.0001365123,0.7904837,0.00003002459,0.0003575648,0.00005686839,0.000007907564,0.00007422724,0.0002144129],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.605778,"threshold_uncertainty_score":0.9999502,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8559835100558566,"score_gpt":0.644237374207395,"score_spread":0.2117461358484616,"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."}}