{"id":"W2810813567","doi":"10.1016/j.jval.2018.04.059","title":"Consumer Preferences for Precision Medicine Technologies: Evidence from A Discrete Choice Experiment","year":2018,"lang":"en","type":"article","venue":"Value in Health","topic":"Health Systems, Economic Evaluations, Quality of Life","field":"Economics, Econometrics and Finance","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Respondent; Medical Expenditure Panel Survey; Context (archaeology); Mixed logit; Willingness to pay; Health care; Actuarial science; Population; Econometrics; Life expectancy; Medicine; Statistics; Logistic regression; Environmental health; Economics; Mathematics; Geography","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":[0.01838409,0.0006774347,0.001033176,0.000469682,0.0005077544,0.002314886,0.0006341073,0.003460726,0.01120767],"category_scores_gemma":[0.07987869,0.0005143522,0.001388687,0.000623056,0.002035504,0.002179053,0.000667194,0.002447456,0.0005728681],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007070774,"about_ca_system_score_gemma":0.0004623683,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001157278,"about_ca_topic_score_gemma":0.0005357742,"domain_scores_codex":[0.9885437,0.009088123,0.0004159205,0.0005976743,0.0011353,0.0002192795],"domain_scores_gemma":[0.7393388,0.2449158,0.009084555,0.004486318,0.001084501,0.001090002],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"randomized_trial","study_design_gemma":"observational","study_design_scores_codex":[0.3991814,0.06218779,0.2527614,0.004262543,0.01000997,0.0008664953,0.005748894,0.01521635,0.01311504,0.03251274,0.006909467,0.197228],"study_design_scores_gemma":[0.1119197,0.1124434,0.5017521,0.002026504,0.01211083,0.002145304,0.005744332,0.07702819,0.01564665,0.1364125,0.02185883,0.0009115172],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9908984,0.0008830832,0.002664132,0.00119227,0.00006499392,0.0001693185,0.0002492082,0.00001143091,0.003867306],"genre_scores_gemma":[0.9958773,0.0004737603,0.001899715,0.0005412595,0.00004455512,0.0001279734,0.0002244959,0.000008194193,0.0008027795],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01838409,"threshold_uncertainty_score":0.09722555,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6293071375630176,"score_gpt":0.5050231840894309,"score_spread":0.1242839534735867,"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."}}