{"id":"W2616441786","doi":"10.1177/0962280217708673","title":"Prediction accuracy for the cure probabilities in mixture cure models","year":2017,"lang":"en","type":"article","venue":"Statistical Methods in Medical Research","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Censoring (clinical trials); Estimator; Cure rate; Statistics; Identifiability; Inverse probability; Computer science; Mathematics; Bayesian probability; Medicine; Posterior probability; Surgery","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":[0.0287784,0.001359728,0.002217972,0.003378934,0.0007090383,0.002522902,0.002059594,0.002428076,0.001888921],"category_scores_gemma":[0.1014022,0.0007008804,0.002163152,0.001699177,0.001498432,0.003071778,0.002581998,0.003479388,0.0006803896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009356755,"about_ca_system_score_gemma":0.0009137906,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0030434,"about_ca_topic_score_gemma":0.002110986,"domain_scores_codex":[0.9901788,0.005483182,0.0006134241,0.001923042,0.001360182,0.0004413855],"domain_scores_gemma":[0.8960623,0.0899533,0.005043711,0.005286782,0.002905802,0.0007481743],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000915687,0.0001940608,0.0986091,0.0003060843,0.0008694411,0.0002418674,0.0006079215,0.6948866,0.001796741,0.02580791,0.00271298,0.1730516],"study_design_scores_gemma":[0.00002174288,0.00009908043,0.00833666,0.00006727283,0.0001019043,0.0001620812,0.00006200087,0.9670692,0.0007746157,0.02255084,0.0006913377,0.00006318124],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1664264,0.001497335,0.8276371,0.0009232641,0.0001047137,0.0001406118,0.0007391915,0.000845578,0.001685793],"genre_scores_gemma":[0.8932812,0.0006757174,0.1024234,0.0002175519,0.0001259375,0.0002054361,0.001622587,0.0001399229,0.001308206],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0287784,"threshold_uncertainty_score":0.1521966,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1801386362180714,"score_gpt":0.545927531221922,"score_spread":0.3657888950038506,"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."}}