{"id":"W1984130041","doi":"10.1111/j.0006-341x.2000.00237.x","title":"A Nonparametric Mixture Model for Cure Rate Estimation","year":2000,"lang":"en","type":"article","venue":"Biometrics","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":445,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Memorial University of Newfoundland; Newcastle University","keywords":"Covariate; Nonparametric statistics; Proportional hazards model; Parametric statistics; Econometrics; Statistics; Parametric model; Nonparametric regression; Semiparametric model; Estimation; Semiparametric regression; Accelerated failure time model; Regression analysis; Mixture model; Computer science; Mathematics; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01542867,0.001295783,0.002799726,0.002863314,0.0008944925,0.002319311,0.00445581,0.00288021,0.004574051],"category_scores_gemma":[0.04882514,0.001222216,0.002761834,0.003479244,0.002046116,0.003844136,0.002523195,0.004238097,0.001778464],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001426382,"about_ca_system_score_gemma":0.001858689,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005438573,"about_ca_topic_score_gemma":0.003564512,"domain_scores_codex":[0.9921112,0.005244627,0.0002514879,0.00100952,0.001094195,0.0002889639],"domain_scores_gemma":[0.9814586,0.01446313,0.001061628,0.001538644,0.001262637,0.0002153965],"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":[0.0002070261,0.0001059846,0.003912287,0.0003601172,0.0003670544,0.000223007,0.0003494384,0.4206326,0.0009154744,0.4238777,0.005471476,0.1435779],"study_design_scores_gemma":[0.00003232182,0.00004752505,0.0007335446,0.00004790341,0.00005617915,0.0001779191,0.00002961235,0.8666368,0.000216608,0.1265633,0.005406276,0.00005213954],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001424269,0.0002829834,0.9975073,0.0001568593,0.00003071822,0.00003858399,0.0000872261,0.0001081505,0.0003638479],"genre_scores_gemma":[0.201936,0.00231484,0.7825186,0.0004767318,0.000435392,0.001447478,0.001774121,0.000316483,0.008780272],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01542867,"threshold_uncertainty_score":0.0815956,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03025689618870801,"score_gpt":0.2980956773642959,"score_spread":0.2678387811755879,"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."}}