{"id":"W2094955313","doi":"10.1007/s001810100115","title":"New directions in business cycle research and financial analysis","year":2002,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Monetary Policy and Economic Impact","field":"Economics, Econometrics and Finance","cited_by":71,"is_retracted":false,"has_abstract":false,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Variety (cybernetics); State space; Econometrics; Inference; Computer science; Business cycle; Markov chain; Autoregressive conditional heteroskedasticity; Section (typography); Mathematical economics; Economics; Mathematics; Artificial intelligence; Statistics; Machine learning; Macroeconomics; Volatility (finance)","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":[0.01162495,0.001301171,0.003431558,0.006315744,0.001460139,0.01086937,0.003313971,0.008202913,0.02446089],"category_scores_gemma":[0.03420162,0.0009092833,0.001419556,0.008398197,0.008576273,0.02322815,0.002985948,0.00892196,0.003906927],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003508905,"about_ca_system_score_gemma":0.004519812,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003313607,"about_ca_topic_score_gemma":0.004214739,"domain_scores_codex":[0.996461,0.001790221,0.0002327828,0.0004035489,0.0009187267,0.0001937806],"domain_scores_gemma":[0.9407565,0.04764492,0.00170741,0.002722985,0.005393229,0.001774892],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001192366,0.0004042025,0.002372911,0.001759606,0.0001024827,0.000117475,0.0003094146,0.001691673,0.000307449,0.7057486,0.08140546,0.2056615],"study_design_scores_gemma":[0.00004741667,0.00002566005,0.0008265058,0.0004817438,0.00003319683,0.00007573847,0.0004009185,0.003692265,0.00005384544,0.8958479,0.09847978,0.00003503362],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.003951226,0.6942607,0.07864976,0.179637,0.01188264,0.00005171252,0.0003059782,0.0003146912,0.03094631],"genre_scores_gemma":[0.08463439,0.7193627,0.07762028,0.03079974,0.06777612,0.0003263817,0.0006926258,0.0002738368,0.01851389],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02446089,"threshold_uncertainty_score":0.08182979,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2122154188907729,"score_gpt":0.3160288153524136,"score_spread":0.1038133964616408,"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."}}