{"id":"W2325076983","doi":"10.4310/sii.2010.v3.n4.a4","title":"Empirical likelihood confidence intervals for ratio of hazard rates under right censorship","year":2010,"lang":"en","type":"article","venue":"Statistics and Its Interface","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Confidence interval; Statistics; Hazard ratio; Censorship; Empirical likelihood; Mathematics; Econometrics; Likelihood-ratio test; Political science; Law","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":[],"consensus_categories":[],"category_scores_codex":[0.0002516076,0.000149148,0.000345499,0.00004756347,0.00004195035,0.00003107875,0.0001114063,0.00007150049,0.0004520039],"category_scores_gemma":[0.001030718,0.0001223538,0.00004200306,0.00005790918,0.0001482612,0.00006190776,0.00006093108,0.0001878439,0.00002737827],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001207763,"about_ca_system_score_gemma":0.0001069218,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000800381,"about_ca_topic_score_gemma":0.0001124162,"domain_scores_codex":[0.9989688,0.0000412944,0.0003499679,0.0002675296,0.0001574256,0.0002149199],"domain_scores_gemma":[0.9985577,0.0004854457,0.0001298066,0.000244136,0.0004043923,0.0001784551],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.004117697,0.001312136,0.04076177,0.003866732,0.001016275,0.00008590902,0.00284666,0.00003431903,0.3963942,0.2474009,0.289621,0.01254249],"study_design_scores_gemma":[0.009916447,0.00416851,0.234366,0.001272548,0.0007817149,0.0001638055,0.0008497698,0.04819671,0.5517104,0.0752306,0.07184217,0.001501297],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6657907,0.0006462855,0.322935,0.001447398,0.0007458393,0.0008673704,0.006631896,0.00005973559,0.0008757683],"genre_scores_gemma":[0.98682,0.00004305379,0.01177181,0.0003131468,0.0000700961,0.00001394048,0.0001251607,0.00002144759,0.0008213751],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3210292,"threshold_uncertainty_score":0.4989442,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03331059000405925,"score_gpt":0.3690655084089494,"score_spread":0.3357549184048901,"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."}}