{"id":"W1605484689","doi":"10.1002/9781118763070.ch7","title":"Statistical analysis of recurrent adverse events","year":2014,"lang":"en","type":"other","venue":"","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Adverse effect; Notation; Event (particle physics); Computer science; Sample size determination; Regression; Clinical trial; Statistics; Regression analysis; Medicine; Intensive care 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.041359,0.0009951992,0.00176813,0.00297203,0.0003620114,0.001762003,0.001736263,0.0007845856,0.0196396],"category_scores_gemma":[0.1988518,0.0003396794,0.002052945,0.003866406,0.001253982,0.001650065,0.001409398,0.002914239,0.003812532],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00107557,"about_ca_system_score_gemma":0.002365352,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008900971,"about_ca_topic_score_gemma":0.0008746706,"domain_scores_codex":[0.9689009,0.01992282,0.001828324,0.002726843,0.006246447,0.0003747008],"domain_scores_gemma":[0.8415114,0.1307003,0.009604102,0.01211926,0.005509994,0.0005549492],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001390319,0.0003199888,0.02491236,0.004294028,0.002708203,0.0003417756,0.0005643758,0.02615175,0.001390643,0.1458142,0.1094041,0.6827083],"study_design_scores_gemma":[0.0005303788,0.002775927,0.04472442,0.002744971,0.001811865,0.001255653,0.00046349,0.1526638,0.004978356,0.4956825,0.2921746,0.0001940988],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01368014,0.007785398,0.9436973,0.00222099,0.0007753854,0.002235553,0.01331154,0.002413003,0.01388075],"genre_scores_gemma":[0.256366,0.01323373,0.6699579,0.002142544,0.001551342,0.01486553,0.01821877,0.002294063,0.02137016],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.041359,"threshold_uncertainty_score":0.2187299,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4749204601491246,"score_gpt":0.5935420984753306,"score_spread":0.1186216383262059,"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."}}