{"id":"W2954511636","doi":"10.1016/j.jval.2019.04.1412","title":"PNS52 CAN COST-EFFECTIVENESS ANALYSIS INFORM THE EXTENT OF COVERAGE UNDER PUBLIC HEALTHCARE? A MICROSIMULATION MODEL OF ALTERNATIVE PRENATAL SCREENING AND DIAGNOSTIC STRATEGIES","year":2019,"lang":"en","type":"article","venue":"Value in Health","topic":"Prenatal Screening and Diagnostics","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Centre for Advancing Health Outcomes; University of British Columbia","funders":"","keywords":"Medicine; Prenatal screening; Cost-effectiveness analysis; Microsimulation; Population; Cost effectiveness; Quality-adjusted life year; Gynecology; Obstetrics; Pregnancy; Statistics; Prenatal diagnosis; Risk analysis (engineering); Fetus; Environmental health; Mathematics; Biology","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":[0.006792409,0.001242033,0.002832058,0.001290291,0.0003198183,0.002533924,0.00191185,0.001897056,0.01577144],"category_scores_gemma":[0.02516351,0.0009007981,0.002479835,0.001323501,0.000979704,0.003076934,0.0009428783,0.001971505,0.0006635219],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004045481,"about_ca_system_score_gemma":0.004008182,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02075305,"about_ca_topic_score_gemma":0.01043457,"domain_scores_codex":[0.9965912,0.002459597,0.00007245826,0.000310103,0.0001977099,0.0003689918],"domain_scores_gemma":[0.9898829,0.008766572,0.0006023318,0.0002592347,0.0003258966,0.0001631029],"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":[0.0004281495,0.0001729042,0.002871391,0.0001360297,0.0003254103,0.00006911689,0.00005837615,0.9256047,0.0002125118,0.04934689,0.001281344,0.01949324],"study_design_scores_gemma":[0.0001374724,0.0003922615,0.002391297,0.00008801554,0.0003101556,0.00006299793,0.00009057645,0.9429607,0.0002015088,0.05110017,0.002236778,0.00002797466],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3868247,0.003231016,0.5221944,0.01973328,0.0003874554,0.001680101,0.00782536,0.0006200115,0.05750367],"genre_scores_gemma":[0.96316,0.0009449063,0.02188679,0.0008570717,0.00009516881,0.0006396364,0.0007235316,0.00005401847,0.01163881],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02075305,"threshold_uncertainty_score":0.05276078,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07238440788601408,"score_gpt":0.3416837077488114,"score_spread":0.2692992998627973,"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."}}