{"id":"W2595890985","doi":"10.1093/jjfinec/nbx006","title":"Rejoinder on: Nonparametric Tail Risk, Stock Returns, and the Macroeconomy","year":2017,"lang":"en","type":"article","venue":"Journal of Financial Econometrics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Nonparametric statistics; Stock (firearms); Econometrics; Perspective (graphical); Point (geometry); Economics; Regression; Actuarial science; Computer science; Mathematics; Statistics; Engineering","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"],"consensus_categories":[],"category_scores_codex":[0.004474516,0.0003265738,0.001249535,0.001519139,0.0009257184,0.0006481722,0.001122856,0.0002427358,0.0003792031],"category_scores_gemma":[0.006724946,0.0002752038,0.0004982182,0.0003461335,0.0004750587,0.001029889,0.0001745227,0.0009350569,0.0003351593],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002320722,"about_ca_system_score_gemma":0.00008222571,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004272921,"about_ca_topic_score_gemma":0.00003617298,"domain_scores_codex":[0.997122,0.00005714416,0.001797863,0.000428291,0.00006799915,0.0005266303],"domain_scores_gemma":[0.9927862,0.0006717289,0.005217427,0.000989377,0.00005550959,0.0002798165],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001238669,0.0003105555,0.7450888,0.00007198418,0.0005340977,0.00006101455,0.00108277,0.001714785,3.991642e-7,0.1645313,0.03137808,0.05398758],"study_design_scores_gemma":[0.007619505,0.0006503933,0.7812563,0.00003317149,0.00006501665,0.0001455387,0.00005762711,0.003527213,0.00001714761,0.06699699,0.1390259,0.0006052452],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9620527,0.006121824,0.0007085172,0.004084162,0.002128331,0.0003441585,0.0002364872,0.00001011767,0.02431368],"genre_scores_gemma":[0.9918875,0.004328499,0.0006117217,0.0011677,0.001046324,0.000008143874,0.000001675285,0.000034234,0.0009142736],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1076478,"threshold_uncertainty_score":0.99997,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09890273097241006,"score_gpt":0.2396905257005058,"score_spread":0.1407877947280957,"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."}}