{"id":"W3122560572","doi":"","title":"Carbon Emissions and Business Cycles","year":2016,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Energy, Environment, Economic Growth","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"","keywords":"Dynamic stochastic general equilibrium; Shock (circulatory); Economics; Business cycle; Greenhouse gas; Autoregressive model; Econometrics; Monetary economics; Vector autoregression; Download; Recession; Investment (military); Macroeconomics; Monetary policy","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":[0.0002942726,0.0002226472,0.0001879927,0.0009692669,0.0002155943,0.002259322,0.0001340905,0.0008552285,0.01008342],"category_scores_gemma":[0.002804947,0.0001215726,0.0001826083,0.001751401,0.0004568284,0.001482566,0.0004003062,0.0008425167,0.001079977],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008012665,"about_ca_system_score_gemma":0.000470513,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003400506,"about_ca_topic_score_gemma":0.003286166,"domain_scores_codex":[0.9998912,0.0000418008,0.000006532505,0.00001992426,0.00002631006,0.0000141471],"domain_scores_gemma":[0.9986898,0.0007708239,0.0003002263,0.00004633164,0.000109686,0.00008314513],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0003461669,0.0002829033,0.1007427,0.0002917492,0.0002945575,0.0008740153,0.0004517684,0.04708145,0.001219498,0.7183113,0.03673865,0.09336523],"study_design_scores_gemma":[0.00003091191,0.00006826523,0.05628718,0.0002383445,0.0001116146,0.0002796996,0.0007286255,0.0349071,0.000781103,0.820132,0.08638686,0.00004839955],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6493198,0.04182609,0.01015277,0.0514022,0.0009919434,0.00002249004,0.002898986,0.0001625105,0.2432231],"genre_scores_gemma":[0.9678695,0.009825543,0.0002563687,0.0003705392,0.0003378157,0.000007454259,0.0003683602,0.00002338313,0.02094096],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01008342,"threshold_uncertainty_score":0.03373235,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01050181279494352,"score_gpt":0.1883113764649931,"score_spread":0.1778095636700495,"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."}}