{"id":"W1812765017","doi":"10.1177/0272989x15604158","title":"Lessons Learned from a Cross-Model Validation between a Discrete Event Simulation Model and a Cohort State-Transition Model for Personalized Breast Cancer Treatment","year":2015,"lang":"en","type":"article","venue":"Medical Decision Making","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University of Alberta","funders":"","keywords":"Breast cancer; Medicine; Cohort; Quality-adjusted life year; Actuarial science; Computer science; Cost effectiveness; Cancer; Risk analysis (engineering); Internal medicine; Economics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.007945113,0.0002587276,0.0009275977,0.0002107651,0.0002608599,0.0001712979,0.0001723944,0.0002592633,0.00009575299],"category_scores_gemma":[0.001973212,0.000272663,0.0001599567,0.0001066814,0.00009112061,0.0005634946,0.00005227963,0.0001445153,0.00003910607],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0011783,"about_ca_system_score_gemma":0.000537169,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005677972,"about_ca_topic_score_gemma":0.000187346,"domain_scores_codex":[0.9957593,0.0001564507,0.002445705,0.0008292352,0.0004264191,0.0003828601],"domain_scores_gemma":[0.9966676,0.001429955,0.0009572355,0.0003257362,0.000174809,0.000444688],"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":[0.0002583122,0.00005802495,0.01268703,0.00004004933,0.00008086453,4.656922e-7,0.004001433,0.9686595,0.000001413033,0.001950555,0.0002816506,0.01198072],"study_design_scores_gemma":[0.002620796,0.00004023137,0.004743806,0.0002010681,0.00003617548,8.567549e-7,0.00009711278,0.8363389,7.272793e-7,0.1555325,0.0001519717,0.0002358851],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3919458,0.0002442441,0.595158,0.009303896,0.00007878761,0.0006270981,0.002588125,0.00003318097,0.00002082483],"genre_scores_gemma":[0.9789276,0.0001736327,0.01820542,0.001527095,0.0002278347,0.0003474062,0.0003102433,0.00004780163,0.0002329763],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5869818,"threshold_uncertainty_score":0.9999726,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5411688471614783,"score_gpt":0.5412581120805278,"score_spread":0.00008926491904948097,"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."}}