{"id":"W3006396558","doi":"10.1002/sim.8495","title":"A hierarchical testing approach for detecting safety signals in clinical trials","year":2020,"lang":"en","type":"article","venue":"Statistics in Medicine","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"National Cancer Institute; National Institute of General Medical Sciences; Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Clinical trial; Data mining; Safety monitoring; Curse of dimensionality; Class (philosophy); Artificial intelligence; Medicine; Bioinformatics","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":[0.07828288,0.0003567176,0.003343627,0.0001746889,0.00007973493,0.00002193914,0.0004589522,0.0003613942,0.0001907921],"category_scores_gemma":[0.9464482,0.0002815934,0.0001573908,0.0008786796,0.0005528857,0.00003675054,0.0001493061,0.001540236,0.000004855847],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008662988,"about_ca_system_score_gemma":0.0001788388,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002411831,"about_ca_topic_score_gemma":0.00001319039,"domain_scores_codex":[0.9817003,0.008138868,0.007718976,0.0009863504,0.0007312799,0.0007242247],"domain_scores_gemma":[0.4526255,0.5453329,0.001027617,0.0003614764,0.000222078,0.0004304409],"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":[0.004499285,0.0008710106,0.008757249,0.002631785,0.0002107896,0.0002335588,0.001925873,0.0003148848,0.0006887533,0.3041283,0.01027445,0.6654641],"study_design_scores_gemma":[0.00796526,0.001221907,0.001165425,0.0004034668,0.0001636984,0.000004026003,0.000331703,0.1398226,0.00003100501,0.848399,0.0001984431,0.0002933991],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0008180633,0.00005646465,0.9924365,0.001646194,0.0004867069,0.002257418,0.0004674259,0.00008525635,0.001745944],"genre_scores_gemma":[0.02328137,0.00003211348,0.9729939,0.001377771,0.002035845,0.0001670966,0.00001974485,0.00007289038,0.00001927647],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8681654,"threshold_uncertainty_score":0.9999636,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8299342855077583,"score_gpt":0.649968645019091,"score_spread":0.1799656404886673,"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."}}