{"id":"W3116180724","doi":"10.3390/jrfm14010012","title":"COVID-19 Outbreak and CO2 Emissions: Macro-Financial Linkages","year":2020,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Greenhouse gas; Volatility (finance); Macro; Outbreak; Stock (firearms); Financial crisis; Econometrics; Economics; 2019-20 coronavirus outbreak; Business; Environmental science; Geography; Macroeconomics; Computer science; Medicine; Ecology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.003573425,0.0004495609,0.0005235191,0.001386594,0.0004479412,0.001708593,0.0008916733,0.0008467457,0.002262253],"category_scores_gemma":[0.01508144,0.0002672697,0.0007032623,0.001929049,0.0008742164,0.00121806,0.001540924,0.001193521,0.0001662709],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008637992,"about_ca_system_score_gemma":0.0007839234,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01944399,"about_ca_topic_score_gemma":0.01292035,"domain_scores_codex":[0.9988372,0.0005330899,0.00005972194,0.0002954659,0.0001134547,0.0001609991],"domain_scores_gemma":[0.9914809,0.004515807,0.002609806,0.0005380747,0.000467626,0.0003877052],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001975199,0.0001351573,0.8396625,0.00008861568,0.0005967886,0.0004582384,0.0001898325,0.08982944,0.0005652647,0.04849843,0.002861124,0.01691703],"study_design_scores_gemma":[0.00002767596,0.0001589442,0.19522,0.00004788604,0.0001877231,0.0002109722,0.0002954067,0.7659981,0.0008393612,0.03402479,0.002915184,0.00007382291],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9378584,0.001036853,0.05155688,0.002520211,0.0001023028,0.00007585445,0.003326216,0.0001265287,0.003396783],"genre_scores_gemma":[0.9953263,0.0001700273,0.002889789,0.0001042383,0.00004886537,0.00003225682,0.0008960738,0.000008233742,0.0005242077],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01944399,"threshold_uncertainty_score":0.0386616,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01964872165641785,"score_gpt":0.2309832610925311,"score_spread":0.2113345394361133,"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."}}