{"id":"W2168722699","doi":"10.1002/cjs.5550340202","title":"Survival analysis based on the proportional hazards model and survey data","year":2006,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Weighting; Econometrics; Computer science; Survey data collection; Sampling (signal processing); Statistics; Sampling design; Missing data; Proportional hazards model; Data mining; Mathematics; Sociology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002435225,0.0001144969,0.0002892311,0.0001821952,0.0001490102,0.00009631451,0.0003315175,0.00004341882,0.000253628],"category_scores_gemma":[0.006816289,0.00007668634,0.00003234373,0.0002748219,0.0001914103,0.000041296,0.00001677086,0.0002209504,0.000001300568],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005375402,"about_ca_system_score_gemma":0.001385381,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005308187,"about_ca_topic_score_gemma":0.09027876,"domain_scores_codex":[0.9985553,0.000270378,0.0004718279,0.0001384886,0.0003550162,0.0002090101],"domain_scores_gemma":[0.9951071,0.003537413,0.0002754713,0.0003562527,0.0004494028,0.000274416],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002833227,0.00004665843,0.04852415,0.0000266538,0.0001944265,0.0001029435,0.00003604851,0.004340714,0.000003192772,0.8914344,0.0523621,0.002900419],"study_design_scores_gemma":[0.0001411013,0.00005200793,0.1289286,0.00001504067,0.0002776859,0.000005110458,0.00001649488,0.5643941,0.000001835177,0.3059223,0.000144016,0.0001017103],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008461531,0.00002079895,0.9798008,0.0003665335,0.00009135227,0.00006340095,0.01033848,0.000002270426,0.0008547935],"genre_scores_gemma":[0.6003927,0.000002502485,0.39922,0.0001247331,0.0000567783,6.872968e-7,0.0001092349,0.00001134769,0.00008194739],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5919312,"threshold_uncertainty_score":0.9263213,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2590261621513028,"score_gpt":0.3557593213831456,"score_spread":0.09673315923184278,"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."}}