{"id":"W2115534608","doi":"10.3386/w8379","title":"Monetary Policy in a Data-Rich Environment","year":2001,"lang":"en","type":"report","venue":"National Bureau of Economic Research","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":74,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal","funders":"","keywords":"Monetary policy; Computer science; Economics; Monetary economics","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":["insufficient_payload"],"category_scores_codex":[0.0109498,0.0004183761,0.001368772,0.003963911,0.0001106931,0.0000890781,0.001889537,0.0006747029,0.004849914],"category_scores_gemma":[0.001257851,0.0005355165,0.0002119267,0.0003522977,0.0003145284,0.000591106,0.0008104434,0.001198498,0.004601851],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00540205,"about_ca_system_score_gemma":0.001647781,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04842691,"about_ca_topic_score_gemma":0.001018755,"domain_scores_codex":[0.9945434,0.0001096257,0.002447324,0.001471631,0.0004142776,0.001013743],"domain_scores_gemma":[0.996583,0.0005616652,0.0009766909,0.001580558,0.00007271699,0.0002253002],"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":[0.0001718458,0.0007950058,0.08741209,0.0004992321,0.001078182,0.00004819896,0.0003679627,0.03741011,0.000006297103,0.3426804,0.5261458,0.003384849],"study_design_scores_gemma":[0.0009148931,0.00009584298,0.01417302,0.00006632997,0.000007485436,0.00003607617,0.00002967817,0.01110002,0.000007020515,0.484554,0.4884185,0.0005971642],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01395559,0.008535022,0.00001450753,0.002702463,0.0005523138,0.000895341,0.004570877,0.00001806752,0.9687558],"genre_scores_gemma":[0.9206137,0.03226654,0.0004502367,0.0001969546,0.004219996,0.0001613396,0.005728291,0.0001687306,0.0361942],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9325616,"threshold_uncertainty_score":0.9997097,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5886896575425815,"score_gpt":0.4775663978484087,"score_spread":0.1111232596941729,"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."}}