{"id":"W7100136488","doi":"","title":"Appendix to Long-Run Monetary Neutrality and Long-Horizon Regressions†","year":2015,"lang":"en","type":"article","venue":"","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Monte Carlo method; Neutrality; Regression; Test (biology); Statistical hypothesis testing","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001761423,0.0008889333,0.001001488,0.002304601,0.0007554938,0.001141044,0.001257771,0.0007011045,0.3733181],"category_scores_gemma":[0.03026076,0.0005192871,0.0006633442,0.003753694,0.000194745,0.0008873541,0.0006883043,0.001796746,0.1190556],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002351361,"about_ca_system_score_gemma":0.004407518,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0434,"about_ca_topic_score_gemma":0.0356782,"domain_scores_codex":[0.9986614,0.0003108058,0.000148808,0.0001560492,0.00063223,0.00009068665],"domain_scores_gemma":[0.9768065,0.01192416,0.001062362,0.001649583,0.008208434,0.000349042],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002895617,0.00006477557,0.001467836,0.0001987954,0.00002036239,0.00005524846,0.00002104835,0.002398534,0.0000775705,0.0142874,0.9575129,0.02386664],"study_design_scores_gemma":[0.0001826529,0.00007598512,0.01788563,0.0004736993,0.00004538612,0.000319948,0.0001197479,0.008980262,0.0006292942,0.06223771,0.9089686,0.00008107587],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.003375902,0.001415101,0.05804199,0.003890096,0.001753724,0.001098295,0.8261565,0.001951242,0.1023172],"genre_scores_gemma":[0.0627908,0.004442821,0.08080243,0.002481837,0.00215151,0.003566365,0.671031,0.001920412,0.1708129],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.6266819,"threshold_uncertainty_score":0.8938856,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1078672079896233,"score_gpt":0.2643025131347734,"score_spread":0.15643530514515,"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."}}