{"id":"W1972232770","doi":"10.1002/jae.1224","title":"When Kahneman meets Manski: Using dual systems of reasoning to interpret subjective expectations of equity returns","year":2010,"lang":"en","type":"article","venue":"Journal of Applied Econometrics","topic":"Financial Markets and Investment Strategies","field":"Economics, Econometrics and Finance","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ministerio de Ciencia y Tecnología; Universitat de Barcelona; Université Laval","keywords":"Sketch; Economics; Dual (grammatical number); Equity (law); Econometrics; Simple (philosophy); Actuarial science; Computer science; Epistemology; Philosophy; Political science","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":[0.01753921,0.0007569909,0.00123423,0.002869128,0.001300843,0.007735381,0.001806651,0.003337876,0.004205308],"category_scores_gemma":[0.06799943,0.0009545712,0.00230937,0.001390042,0.009239864,0.01526754,0.004559448,0.003912058,0.0006948664],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002706876,"about_ca_system_score_gemma":0.001601926,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002918262,"about_ca_topic_score_gemma":0.001678191,"domain_scores_codex":[0.9899422,0.005349576,0.0008932457,0.001249012,0.001774559,0.0007913964],"domain_scores_gemma":[0.9721028,0.0182896,0.004207128,0.002539141,0.001939884,0.0009214529],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001296986,0.00004263569,0.003726205,0.00006975765,0.00007429133,0.0003096606,0.003072728,0.00644892,0.0005245848,0.9764073,0.0007593791,0.008434898],"study_design_scores_gemma":[0.00002037684,0.00001608851,0.0004934838,0.00001955414,0.00001565113,0.00008947652,0.0003410646,0.03284759,0.0001643164,0.9652501,0.0007179931,0.00002425056],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1896534,0.0006373519,0.7644991,0.01003998,0.00026454,0.0001823775,0.0002279405,0.000159609,0.03433567],"genre_scores_gemma":[0.9143494,0.0001639902,0.08281737,0.0005799281,0.0001194112,0.0001420051,0.0001032757,0.00003302578,0.001691521],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01753921,"threshold_uncertainty_score":0.09275734,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04612736372084098,"score_gpt":0.2603991884974109,"score_spread":0.21427182477657,"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."}}