{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.07009605,0.001812652,0.002713984,0.004316766,0.001321322,0.001855291,0.004036479,0.002086674,0.004508461],"category_scores_gemma":[0.1723125,0.0009033388,0.003364968,0.003688881,0.004505774,0.002569905,0.00292022,0.003811558,0.0007224472],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002391848,"about_ca_system_score_gemma":0.00411437,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005251084,"about_ca_topic_score_gemma":0.004695704,"domain_scores_codex":[0.9145066,0.069721,0.002328416,0.005585645,0.00675907,0.001099277],"domain_scores_gemma":[0.7102125,0.2558574,0.01049512,0.01523175,0.006365923,0.001837248],"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":[0.001307955,0.0004156676,0.03022074,0.001311029,0.002877695,0.001044411,0.001298663,0.2517477,0.004456624,0.3229701,0.007178493,0.3751709],"study_design_scores_gemma":[0.000309186,0.0008968038,0.005044808,0.00009852582,0.0003537654,0.0002173788,0.0000705336,0.7115688,0.001279531,0.2777798,0.002316157,0.00006471927],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005614107,0.0002411763,0.9922534,0.0004355438,0.0000457943,0.0002953013,0.0002007582,0.0002762962,0.0006377448],"genre_scores_gemma":[0.3427007,0.0003274491,0.6515617,0.0007867751,0.0003490148,0.002194357,0.0006812796,0.0001236332,0.001275021],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9299039,"threshold_uncertainty_score":0.3707078,"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."}}