{"id":"W3123191407","doi":"","title":"Forecast Performance of Neural Networks and Business Cycle Asymmetries","year":2005,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Artificial neural network; Business cycle; Sample (material); Econometrics; Series (stratigraphy); Computer science; Nonlinear system; Economics; Artificial intelligence; Macroeconomics","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":[],"consensus_categories":[],"category_scores_codex":[0.007266372,0.0008218795,0.0006521742,0.001324056,0.000261515,0.001396549,0.0004966491,0.001249013,0.001783736],"category_scores_gemma":[0.04224789,0.0003255988,0.000477324,0.001086367,0.0004422867,0.002650623,0.0007254588,0.000880186,0.0002371265],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001284418,"about_ca_system_score_gemma":0.0005080425,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005566223,"about_ca_topic_score_gemma":0.003008845,"domain_scores_codex":[0.9987918,0.0005114571,0.0001142239,0.0001954271,0.0002773879,0.0001097716],"domain_scores_gemma":[0.9682041,0.02653662,0.002316796,0.001053672,0.001628546,0.0002601217],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008216405,0.0001063467,0.04304348,0.00009982965,0.0002824387,0.00009004085,0.0000878491,0.9005478,0.001079954,0.004373739,0.0005351966,0.04893173],"study_design_scores_gemma":[0.00001304657,0.00008123383,0.006521958,0.00001613613,0.00003501947,0.00002059328,0.00002256288,0.9891973,0.0009670887,0.003006118,0.0001057499,0.0000132224],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.9603385,0.001268087,0.03234684,0.0006119527,0.00004983671,0.00003307491,0.0003671289,0.0001273712,0.00485722],"genre_scores_gemma":[0.9965593,0.0002293163,0.002544127,0.00002179771,0.00001766858,0.0000107418,0.0001913024,0.000007871902,0.0004178337],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.007266372,"threshold_uncertainty_score":0.03842872,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01917322438123034,"score_gpt":0.1938285340597676,"score_spread":0.1746553096785372,"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."}}