{"id":"W1987856141","doi":"10.1002/sim.986","title":"Maximum likelihood estimation of a survival function with a change point for truncated and interval‐censored data","year":2002,"lang":"en","type":"article","venue":"Statistics in Medicine","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Statistics; Interval (graph theory); Point estimation; Estimation; Maximum likelihood; Interval estimation; Likelihood function; Survival function; Survival analysis; Confidence interval; Econometrics; Function (biology); Mathematics; Computer science; Biology; Combinatorics; Economics","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":[0.01419077,0.0008797315,0.001910371,0.002071877,0.0005097509,0.001330947,0.002105576,0.002370686,0.001559905],"category_scores_gemma":[0.06232985,0.0007160215,0.001586397,0.001953448,0.002044405,0.003028948,0.001670104,0.002403231,0.0006271059],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001092047,"about_ca_system_score_gemma":0.0009911541,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002122827,"about_ca_topic_score_gemma":0.001220456,"domain_scores_codex":[0.9963441,0.002337377,0.0001779322,0.0005827485,0.0004078894,0.00014995],"domain_scores_gemma":[0.9614891,0.03443103,0.001735854,0.00123844,0.0008628703,0.0002426535],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004983541,0.0001390691,0.00942946,0.0003508222,0.000296581,0.0006070553,0.0004689,0.7452925,0.002194322,0.0977762,0.001565538,0.1413812],"study_design_scores_gemma":[0.00004516618,0.00008697728,0.001646698,0.00004603896,0.0000359199,0.0001679352,0.00003760755,0.9270003,0.0008197612,0.06918421,0.0008867782,0.00004268145],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01241045,0.0003007025,0.9867234,0.0001416448,0.00001615849,0.00002788765,0.00005882751,0.000144822,0.0001761898],"genre_scores_gemma":[0.4142025,0.001380786,0.5795243,0.0001777775,0.0001445674,0.000432826,0.001146746,0.0001502991,0.002840167],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01419077,"threshold_uncertainty_score":0.07504892,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1902006824861012,"score_gpt":0.3979920695445226,"score_spread":0.2077913870584214,"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."}}