{"id":"W3124117302","doi":"10.3982/qe856","title":"Eliciting risk preferences using choice lists","year":2019,"lang":"en","type":"article","venue":"Quantitative Economics","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Lottery; Pairwise comparison; Incentive; Payment; Actuarial science; Econometrics; Computer science; Economics; Microeconomics; Psychology; Artificial intelligence; Finance","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004114319,0.0007554985,0.0005757943,0.0004267,0.0002689956,0.00106565,0.0006510833,0.0009197228,0.006513079],"category_scores_gemma":[0.02908315,0.0004095462,0.0003200998,0.0005485488,0.0005032979,0.002045509,0.0009780253,0.0008563591,0.001517013],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002464795,"about_ca_system_score_gemma":0.0002844187,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002114813,"about_ca_topic_score_gemma":0.000327142,"domain_scores_codex":[0.9961569,0.002614006,0.0001804006,0.0002861363,0.0006134007,0.0001492248],"domain_scores_gemma":[0.9151722,0.07478405,0.004988271,0.002979307,0.00099581,0.001080377],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.02663844,0.01907971,0.07296459,0.002344886,0.0005424377,0.0006293234,0.00473881,0.04046018,0.4300621,0.0278728,0.004122996,0.3705437],"study_design_scores_gemma":[0.005132692,0.0335621,0.1041049,0.0004199701,0.0005899337,0.0007430831,0.002369886,0.4034951,0.3589602,0.07682801,0.01307065,0.0007235564],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.9719949,0.00008401587,0.02540264,0.0001647236,0.00002109303,0.0001262173,0.0001292721,0.0001470633,0.001930104],"genre_scores_gemma":[0.9690267,0.000140464,0.02842214,0.0001541038,0.00003120579,0.0002340072,0.00029359,0.00002953899,0.001668378],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.006513079,"threshold_uncertainty_score":0.02178848,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2975611152905501,"score_gpt":0.4562572243488975,"score_spread":0.1586961090583474,"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."}}