{"id":"W2004939947","doi":"10.1016/j.csda.2007.04.018","title":"Mixture cure models for multivariate survival data","year":2007,"lang":"en","type":"article","venue":"Computational Statistics & Data Analysis","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":70,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"","keywords":"Censoring (clinical trials); Statistics; Covariate; Multivariate statistics; Bivariate analysis; Jackknife resampling; Mathematics; Survival analysis; Marginal model; Survival function; Marginal distribution; Random effects model; Multivariate analysis; Econometrics; Correlation; Regression analysis; Medicine; Random variable; Internal medicine","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":[0.01611769,0.002249335,0.004419452,0.005121386,0.001327464,0.003326473,0.005164266,0.00421744,0.007375],"category_scores_gemma":[0.05860632,0.002252779,0.004955433,0.004927778,0.003099707,0.005008986,0.003835842,0.007797325,0.002839206],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001819675,"about_ca_system_score_gemma":0.001943482,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005169648,"about_ca_topic_score_gemma":0.0062645,"domain_scores_codex":[0.9929182,0.004503089,0.0002909417,0.0009394418,0.001025919,0.0003224125],"domain_scores_gemma":[0.9630874,0.02990106,0.001820376,0.003091937,0.001582143,0.0005170162],"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":[0.0002982837,0.0001126196,0.002056567,0.0003834764,0.0004481173,0.0001587521,0.0006035336,0.3239188,0.0008562331,0.5569621,0.007810086,0.1063915],"study_design_scores_gemma":[0.00003358531,0.00002364478,0.0004160079,0.00005526646,0.0000590075,0.00009621863,0.00002801634,0.6724002,0.0001624927,0.3241323,0.002543925,0.00004937499],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001987224,0.0004860041,0.9965661,0.0002226615,0.00003680658,0.00003229124,0.0001280319,0.0002505591,0.0002902655],"genre_scores_gemma":[0.2070572,0.004428621,0.7653315,0.0006701411,0.00077987,0.002210973,0.003796648,0.001114048,0.01461103],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01611769,"threshold_uncertainty_score":0.08523953,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1092255275723662,"score_gpt":0.3880269756108853,"score_spread":0.278801448038519,"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."}}