{"id":"W2117590223","doi":"10.1002/sim.4392","title":"Relative survival multistate Markov model","year":2011,"lang":"en","type":"article","venue":"Statistics in Medicine","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Canadian Institutes of Health Research","keywords":"Relative survival; Markov model; Proportional hazards model; Survival analysis; Markov chain; Statistics; Hazard ratio; Hazard; Relative risk; Medicine; Econometrics; Computer science; Mathematics; Cancer; Cancer registry; Internal medicine; Biology; Confidence interval","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":[0.006371979,0.001109431,0.001901382,0.00141326,0.0006509455,0.001708401,0.003358264,0.001979443,0.01103724],"category_scores_gemma":[0.01231322,0.0006639109,0.001698523,0.001594922,0.001202834,0.0023003,0.00150875,0.002851697,0.001947878],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001735186,"about_ca_system_score_gemma":0.001797587,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006701079,"about_ca_topic_score_gemma":0.004531111,"domain_scores_codex":[0.9972391,0.001513554,0.0001277277,0.000540996,0.0003144945,0.000264154],"domain_scores_gemma":[0.9920495,0.00597714,0.0006257179,0.0005132326,0.0006400368,0.0001944062],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002450704,0.00008228881,0.004236382,0.0002172782,0.0001603697,0.0002853749,0.0002784629,0.6502979,0.0006036041,0.3144478,0.00392015,0.02522531],"study_design_scores_gemma":[0.00005560513,0.00005518888,0.0004337167,0.00002290513,0.00005175983,0.00008409627,0.00002621748,0.9064733,0.0001493292,0.08991074,0.002711346,0.00002585553],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02037729,0.0007113976,0.9700558,0.001338914,0.0001636068,0.0001798549,0.00207903,0.0006072975,0.00448673],"genre_scores_gemma":[0.7667221,0.002076501,0.2008055,0.0007137722,0.000343296,0.001729246,0.004657374,0.0001583558,0.02279377],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01103724,"threshold_uncertainty_score":0.03692323,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1961461722704344,"score_gpt":0.4247385603319856,"score_spread":0.2285923880615512,"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."}}