{"id":"W3124612177","doi":"10.2139/ssrn.2246914","title":"Uncertainty, Risk, and Incentives: Theory and Evidence","year":2013,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Experimental Behavioral Economics Studies","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Incentive; Actuarial science; Economics; Econometrics; Business; Microeconomics","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":[0.01714058,0.001041908,0.001699178,0.00271903,0.001018791,0.007598801,0.001739368,0.004710107,0.01176697],"category_scores_gemma":[0.09662342,0.0007359525,0.0006457877,0.002705629,0.006552571,0.006988018,0.001888818,0.00271979,0.0006151731],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002150377,"about_ca_system_score_gemma":0.002103338,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002838996,"about_ca_topic_score_gemma":0.001929865,"domain_scores_codex":[0.9940102,0.003175596,0.0003518359,0.0007119363,0.001404858,0.0003455885],"domain_scores_gemma":[0.7233424,0.2512933,0.016818,0.004063732,0.003309054,0.00117347],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.002758277,0.001432351,0.07904284,0.003106711,0.001112197,0.0003760415,0.001270951,0.01522046,0.0006214021,0.6596922,0.00603531,0.2293312],"study_design_scores_gemma":[0.0003999555,0.0002558683,0.03149442,0.001245356,0.0003384968,0.0002377923,0.0009918233,0.007080401,0.000459368,0.9463265,0.01108188,0.00008813953],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4509424,0.2963481,0.04519467,0.06147601,0.0007515447,0.0002678262,0.0008087395,0.0000885827,0.1441222],"genre_scores_gemma":[0.9469447,0.044614,0.00414269,0.002292862,0.000724216,0.00008043422,0.00009959884,0.00001530854,0.00108613],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01714058,"threshold_uncertainty_score":0.09064913,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01639297256249215,"score_gpt":0.3102991515746515,"score_spread":0.2939061790121594,"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."}}