{"id":"W3101438137","doi":"10.20955/wp.2022.024","title":"Dissecting Idiosyncratic Earnings Risk","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Financial Literacy, Pension, Retirement Analysis","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Fundação para a Ciência e a Tecnologia; Norges Forskningsråd","keywords":"Earnings; Systematic risk; Business; Finance","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":[0.00160418,0.0002615053,0.0002903928,0.0009126046,0.0002259539,0.001683052,0.0002791627,0.000362137,0.002669723],"category_scores_gemma":[0.01178779,0.000152352,0.0002876784,0.0008388826,0.0008446822,0.001434201,0.00104355,0.000558327,0.000229723],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004997051,"about_ca_system_score_gemma":0.0003208924,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003270561,"about_ca_topic_score_gemma":0.002524726,"domain_scores_codex":[0.9994561,0.0001764903,0.00003189211,0.0001337937,0.0001082952,0.00009335217],"domain_scores_gemma":[0.9948778,0.002753136,0.001206856,0.0006461338,0.0003244542,0.0001914972],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003121575,0.00008801238,0.5475159,0.00009871829,0.0002651261,0.0009653524,0.002459302,0.07230462,0.003203838,0.2573913,0.002782333,0.1126134],"study_design_scores_gemma":[0.0000256939,0.0001282136,0.4535056,0.00007615532,0.00009834922,0.0004895128,0.001949918,0.2358009,0.001381845,0.3008718,0.005574406,0.00009770278],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9482856,0.0004149836,0.04155377,0.000719977,0.00003107042,0.0000159439,0.0003331696,0.00005934343,0.008586062],"genre_scores_gemma":[0.99738,0.0001723623,0.00124116,0.00002693725,0.00002791048,0.000003237955,0.0001225103,0.000008491531,0.001017437],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003270561,"threshold_uncertainty_score":0.0089311,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01371233470563147,"score_gpt":0.2324692883521884,"score_spread":0.2187569536465569,"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."}}