{"id":"W2064554092","doi":"10.1002/sim.2885","title":"Non‐inferiority trial design for recurrent events","year":2007,"lang":"en","type":"article","venue":"Statistics in Medicine","topic":"Statistical Methods in Clinical Trials","field":"Mathematics","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Sample size determination; Statistics; Poisson distribution; Robustness (evolution); Null hypothesis; Econometrics; Computer science; Event (particle physics); Marginal distribution; Random effects model; Mathematics; Medicine; Random variable; Meta-analysis; 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"],"consensus_categories":[],"category_scores_codex":[0.02121588,0.0002628478,0.001052849,0.0001694294,0.00007271914,0.000007483788,0.0003030854,0.000209179,0.0003391257],"category_scores_gemma":[0.2800786,0.0002128312,0.00006554313,0.0002909525,0.000254342,0.00002716255,0.00005620994,0.0004472358,0.00001328087],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001583191,"about_ca_system_score_gemma":0.0001033227,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001588957,"about_ca_topic_score_gemma":0.00005137249,"domain_scores_codex":[0.9959036,0.0004484713,0.001937616,0.0004486806,0.0006713061,0.000590301],"domain_scores_gemma":[0.8821255,0.1166138,0.0003817018,0.0004102754,0.0002425019,0.0002262402],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.09075569,0.001136023,0.0003486436,0.0007057457,0.000124186,0.0001114424,0.0006665135,0.000003843292,0.0001224731,0.6508883,0.07853328,0.1766039],"study_design_scores_gemma":[0.04351987,0.003831127,0.0006546496,0.0002547278,0.0001303822,0.000001807216,0.00006892767,0.0007737258,0.0001177617,0.9494869,0.0009457775,0.0002143819],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001242605,0.00003050844,0.9901071,0.0002480176,0.004406712,0.002906902,0.0002321741,0.00004292364,0.0007830355],"genre_scores_gemma":[0.007253488,0.00004580872,0.9905825,0.0001766618,0.001559992,0.0001340569,0.00001378236,0.00004583944,0.00018793],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2985986,"threshold_uncertainty_score":0.8679003,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6391600063244661,"score_gpt":0.6329558923146955,"score_spread":0.006204114009770612,"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."}}