{"id":"W1601300195","doi":"10.1628/001522111x614141","title":"Adverse Selection and Risk Aversion in Capital Markets","year":2011,"lang":"en","type":"article","venue":"FinanzArchiv Public Finance Analysis","topic":"Financial Literacy, Pension, Retirement Analysis","field":"Business, Management and Accounting","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Adverse selection; Economics; Risk aversion (psychology); Selection (genetic algorithm); Financial economics; Monetary economics; Microeconomics; Expected utility hypothesis; Computer science","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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009067281,0.0003508192,0.000580872,0.002833777,0.0003760398,0.0001465242,0.0003581464,0.0001254997,0.001050173],"category_scores_gemma":[0.0003399166,0.0003516903,0.0003629522,0.005885962,0.0001112462,0.002298589,0.0003021297,0.0003142575,0.0002670488],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007420457,"about_ca_system_score_gemma":0.00004383357,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008382824,"about_ca_topic_score_gemma":0.01074106,"domain_scores_codex":[0.9974815,0.00006521745,0.0006131485,0.000815094,0.000400722,0.0006242939],"domain_scores_gemma":[0.9987234,0.00005150769,0.0005356103,0.0004459407,0.0002155514,0.00002796482],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00009230613,0.0001573541,0.9889968,0.00003042548,0.0001021399,0.00002073331,0.0002406274,0.00006279049,0.00001640951,0.005715805,0.0005065962,0.004058005],"study_design_scores_gemma":[0.0005461102,0.00001806107,0.9393954,0.00002594804,0.0007828118,0.000001071779,0.00008930831,0.04700747,0.00001201727,0.001951986,0.009780279,0.000389532],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9938633,0.0001142979,0.0004350261,0.00008384745,0.00009310579,0.0002076166,0.00001086525,0.00008985439,0.005102033],"genre_scores_gemma":[0.997301,0.0003731487,0.001151233,0.0001742054,0.0001677614,0.00003637499,0.0001382625,0.00002861992,0.0006293534],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0496014,"threshold_uncertainty_score":0.9998935,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01232043904015675,"score_gpt":0.1910369773591315,"score_spread":0.1787165383189748,"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."}}