{"id":"W2955253476","doi":"10.1016/j.jval.2019.04.361","title":"PCN240 EVALUATING PARTITIONED SURVIVAL MODEL AND RESPONSE-BASED MODELING APPROACHES FOR USE IN COST-EFFECTIVENESS ANALYSIS: ESTIMATING AND VALIDATING SURVIVAL OUTCOMES","year":2019,"lang":"en","type":"article","venue":"Value in Health","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Bristol-Myers Squibb (Canada)","funders":"","keywords":"Sunitinib; Medicine; Survival analysis; Oncology; Progression-free survival; Internal medicine; Overall survival; Renal cell carcinoma; Statistics; Mathematics","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.04732304,0.001227493,0.001015773,0.001365611,0.000412181,0.001258695,0.001732378,0.001046862,0.00958347],"category_scores_gemma":[0.1354401,0.000579678,0.002132217,0.001282385,0.0004845019,0.001081483,0.001492381,0.001259408,0.0007739755],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002022206,"about_ca_system_score_gemma":0.00451943,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02767563,"about_ca_topic_score_gemma":0.0193238,"domain_scores_codex":[0.9787487,0.01795437,0.00057054,0.0009511685,0.001503883,0.000271371],"domain_scores_gemma":[0.8716761,0.1131296,0.002701702,0.005138613,0.006842747,0.0005112318],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004662564,0.001090572,0.02098705,0.001059218,0.002331346,0.0001261593,0.0001967606,0.7643444,0.0007290374,0.0136808,0.01149088,0.1793013],"study_design_scores_gemma":[0.0004331782,0.0008386282,0.003681979,0.0001164763,0.0002787164,0.00004050671,0.00004688356,0.9878583,0.0009549717,0.00363965,0.002087777,0.00002300218],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3881544,0.001207606,0.5736454,0.001174486,0.0002681726,0.002833593,0.01351717,0.002448772,0.01675042],"genre_scores_gemma":[0.7487418,0.0004050536,0.2363392,0.0003145101,0.00004712964,0.00228132,0.008776559,0.0004423362,0.002652162],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.952677,"threshold_uncertainty_score":0.2502711,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.756340347782525,"score_gpt":0.4887053661435728,"score_spread":0.2676349816389522,"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."}}