{"id":"W2954222820","doi":"10.1016/j.jval.2019.04.1552","title":"PNS195 MODELLING HETEROGENEOUS PUBLIC PREFERENCES IN DISCRETE CHOICE EXPERIMENTS: AN APPLICATION TO PRENATAL SCREENING AND DIAGNOSTIC STRATEGIES FOR CHROMOSOMAL ABNORMALITIES","year":2019,"lang":"en","type":"article","venue":"Value in Health","topic":"Economic and Environmental Valuation","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia; Centre for Advancing Health Outcomes","funders":"","keywords":"Population; Miscarriage; Prenatal screening; Medicine; Bayes' theorem; Prenatal diagnosis; Sample (material); Pregnancy; Psychology; Environmental health; Statistics; Bayesian probability; Biology; Genetics","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":[0.01641946,0.001302248,0.003232765,0.001636242,0.0007361497,0.003108287,0.00244239,0.003959146,0.01767928],"category_scores_gemma":[0.04283097,0.001525008,0.002737888,0.002089056,0.00236561,0.003461528,0.002116201,0.003753291,0.0006956235],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002754778,"about_ca_system_score_gemma":0.001841283,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01350708,"about_ca_topic_score_gemma":0.008526136,"domain_scores_codex":[0.9937655,0.005040383,0.0001439805,0.0004940221,0.0002618215,0.0002944005],"domain_scores_gemma":[0.9204625,0.07493376,0.001750722,0.001403819,0.0006461671,0.0008030073],"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":[0.0006643907,0.0003542366,0.004079944,0.0002027576,0.0003488335,0.0003274229,0.0002627234,0.692387,0.0004644271,0.2769665,0.001621376,0.02232047],"study_design_scores_gemma":[0.0001944282,0.00009958474,0.0005658594,0.00002098255,0.00005623894,0.00003030358,0.00004559131,0.8896449,0.00008875397,0.1084825,0.0007465395,0.00002441617],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1347993,0.0006867006,0.8524022,0.002935404,0.0002082416,0.000371915,0.001336683,0.000423602,0.006835987],"genre_scores_gemma":[0.8157835,0.0009521165,0.1556213,0.0005802581,0.0002457792,0.001035663,0.0007975948,0.0001367103,0.02484713],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01767928,"threshold_uncertainty_score":0.08683544,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.149757639033529,"score_gpt":0.281365826387584,"score_spread":0.1316081873540549,"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."}}