{"id":"W1966407078","doi":"10.1081/sta-200063317","title":"Smoothing Techniques for the Bivariate Kaplan–Meier Estimator","year":2005,"lang":"en","type":"article","venue":"Communication in Statistics- Theory and Methods","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Estimator; Bivariate analysis; Mathematics; Smoothing; Kaplan–Meier estimator; Survival function; Statistics; Censoring (clinical trials); Univariate; Kernel smoother; Econometrics; Applied mathematics; Kernel method; Computer science; Multivariate statistics; Artificial intelligence","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":[0.0110257,0.000157293,0.000277674,0.00006830426,0.0003510861,0.00007553754,0.0004233178,0.0000925615,0.00009957073],"category_scores_gemma":[0.01595699,0.0001132065,0.00003068784,0.0001183075,0.0003079291,0.00008136807,0.0001598733,0.0002984173,0.000002186481],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003361162,"about_ca_system_score_gemma":0.00003361149,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001739597,"about_ca_topic_score_gemma":0.00001417055,"domain_scores_codex":[0.996524,0.002492507,0.000485017,0.0001921062,0.00009141634,0.0002149478],"domain_scores_gemma":[0.9463003,0.05265545,0.0001761285,0.0006993274,0.0001121299,0.00005663987],"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":[0.00004113431,0.000025276,0.00001696825,0.00003658553,0.00001087325,1.235637e-7,0.0005366445,0.00000157736,0.000102323,0.5885849,0.0002954061,0.4103482],"study_design_scores_gemma":[0.0002439719,0.00003661819,0.0004522356,0.00009043761,0.00006091749,0.000004992944,0.0002355278,0.0122879,0.0009971652,0.9635707,0.02186758,0.0001519619],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0001063582,0.000904292,0.9961444,0.0005905863,0.00006263008,0.0005012254,0.00010451,0.0000675953,0.001518395],"genre_scores_gemma":[0.009895067,0.0003779174,0.9887848,0.0003330906,0.00004382813,0.0002976198,0.000007890884,0.00002598662,0.0002337776],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4101962,"threshold_uncertainty_score":0.992332,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1162774138752122,"score_gpt":0.5081949354640466,"score_spread":0.3919175215888344,"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."}}