{"id":"W1925128412","doi":"10.1002/fut.21737","title":"Forecasting the LIBOR‐Federal Funds Rate Spread During and After the Financial Crisis","year":2015,"lang":"en","type":"article","venue":"Journal of Futures Markets","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Libor; Predictability; Futures contract; Economics; Financial crisis; Financial economics; Econometrics; Futures market; Federal funds; Econometric model; Financial market; Interest rate; Monetary economics; Finance; Macroeconomics; Monetary policy; Statistics","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":[],"consensus_categories":[],"category_scores_codex":[0.001830158,0.0001443373,0.0003035382,0.0001090977,0.0002281467,0.0002056532,0.0002511172,0.00007336852,0.0001602529],"category_scores_gemma":[0.0003607942,0.00009064612,0.0001485213,0.00007085788,0.00005379384,0.0003876859,0.00007809474,0.0003204496,0.00001580246],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000582528,"about_ca_system_score_gemma":0.00002412372,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008152134,"about_ca_topic_score_gemma":0.0000583503,"domain_scores_codex":[0.9988692,0.00006056588,0.0006073986,0.0001381892,0.00003995895,0.0002847096],"domain_scores_gemma":[0.9989423,0.0001193041,0.0005874569,0.0001932354,0.00002344512,0.0001342989],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.01032627,0.0002537548,0.6009527,0.0002260651,0.001133349,0.0004405968,0.02797411,0.005056457,0.00002972293,0.003946274,0.3303896,0.019271],"study_design_scores_gemma":[0.001344392,0.0001493038,0.9287621,0.00003223187,0.00002567426,0.0006008773,0.0006817088,0.00514832,0.00002758428,0.01523979,0.04772981,0.0002582415],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9854226,0.004829779,0.00005420723,0.005798088,0.0009396157,0.00007722051,0.00002035947,0.000003972136,0.002854172],"genre_scores_gemma":[0.9961542,0.0002645716,0.0001122266,0.001395141,0.001718915,0.000003452142,4.552818e-7,0.00001467809,0.0003362908],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3278093,"threshold_uncertainty_score":0.3696442,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05257934306241516,"score_gpt":0.2187148592981772,"score_spread":0.1661355162357621,"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."}}