{"id":"W2210479457","doi":"","title":"Finding SPF Percentiles Closest to Greenbook","year":2015,"lang":"en","type":"preprint","venue":"","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Booth University College","funders":"","keywords":"Percentile; Inflation (cosmology); Survey of Professional Forecasters; Statistics; Econometrics; Economics; Mathematics; Monetary policy; Keynesian economics; Physics","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":[0.002527049,0.0003627557,0.0006936243,0.002747034,0.0003951387,0.001502376,0.0003878856,0.0007127669,0.003305481],"category_scores_gemma":[0.0174809,0.0001776726,0.0005226329,0.001854548,0.0004367181,0.001497251,0.0009135289,0.001009272,0.001115551],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004191565,"about_ca_system_score_gemma":0.0003798311,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006528902,"about_ca_topic_score_gemma":0.004531171,"domain_scores_codex":[0.9988846,0.0001907642,0.00006605044,0.000331074,0.0002928438,0.0002346878],"domain_scores_gemma":[0.9901044,0.004302118,0.002604877,0.001085847,0.001190353,0.0007124427],"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":[0.0005380186,0.00005934159,0.8868179,0.00009729259,0.0002857173,0.0004961723,0.0005559347,0.03288332,0.001585953,0.003484599,0.01262126,0.06057452],"study_design_scores_gemma":[0.00003675687,0.000253194,0.8761891,0.00009063641,0.00009793339,0.0005343202,0.002141714,0.09014765,0.003383113,0.01101278,0.01600079,0.0001121068],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9811003,0.0008185341,0.008604653,0.0003589485,0.00007472263,0.00001013983,0.004444953,0.0002682691,0.004319375],"genre_scores_gemma":[0.9942114,0.0001231295,0.0006759991,0.00003156336,0.00004865462,0.00000499114,0.004408854,0.00002711927,0.0004682386],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006528902,"threshold_uncertainty_score":0.01336443,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2306970251708467,"score_gpt":0.2804349317262868,"score_spread":0.04973790655544003,"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."}}