{"id":"W4225128199","doi":"10.1016/j.jval.2022.01.012","title":"Accounting for Preference Heterogeneity in Discrete-Choice Experiments: An ISPOR Special Interest Group Report","year":2022,"lang":"en","type":"review","venue":"Value in Health","topic":"Economic and Environmental Valuation","field":"Economics, Econometrics and Finance","cited_by":78,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Preference; Mixed logit; Preference elicitation; Portfolio; Selection (genetic algorithm); Discrete choice; Econometrics; Actuarial science; Accounting; Psychology; Logistic regression; Economics; Computer science; Statistics; Microeconomics; Mathematics; Financial economics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002937363,0.0003442006,0.001575265,0.000413376,0.0001247073,0.00006220129,0.0004227853,0.000189132,0.0005109689],"category_scores_gemma":[0.0001945807,0.0004240097,0.0002489292,0.0001982389,0.00003345467,0.0003995649,0.0001829369,0.0004238613,0.00005925251],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002593845,"about_ca_system_score_gemma":0.0001178224,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004720607,"about_ca_topic_score_gemma":0.0009148402,"domain_scores_codex":[0.9956599,0.0001569077,0.002571661,0.001066672,0.00005024105,0.0004945688],"domain_scores_gemma":[0.9973038,0.0002082354,0.001811721,0.0005657446,0.000002872544,0.0001076051],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005554858,0.001774572,0.2901143,0.02359935,0.0001839023,0.00004917542,0.001815766,0.001571694,1.958885e-7,0.04632493,0.0005612258,0.6339494],"study_design_scores_gemma":[0.0004346566,0.000164724,0.007726193,0.000996949,0.000008415239,0.00001398898,0.00008817898,0.0007055422,1.261556e-7,0.001201197,0.9882193,0.0004406829],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.03616849,0.9579569,0.0002008383,0.000045112,0.001751204,0.002583598,0.0004998554,0.00002361943,0.0007704518],"genre_scores_gemma":[0.003952893,0.9918688,0.0006901449,0.0001146397,0.0008045677,0.001088641,0.00127896,0.00008837241,0.0001129757],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9876581,"threshold_uncertainty_score":0.9998212,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5665849309178793,"score_gpt":0.3834187387557521,"score_spread":0.1831661921621272,"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."}}