{"id":"W3207160090","doi":"","title":"Measuring Financial Impact Of COVID-19 Pandemic On Global Stock Markets -","year":2020,"lang":"en","type":"article","venue":"","topic":"COVID-19 Pandemic Impacts","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Stock market; Stock exchange; Stock (firearms); Spillover effect; Event study; Coronavirus disease 2019 (COVID-19); Pandemic; Timeline; Financial economics; Business; Economics; Monetary economics; Context (archaeology); Finance; Geography; Macroeconomics; Medicine; Internal medicine","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":[0.0008881633,0.0003279806,0.0002477239,0.001332752,0.0002775886,0.001356389,0.0002300625,0.0005028771,0.003406282],"category_scores_gemma":[0.003190126,0.00008459272,0.0003559089,0.001128957,0.0003115917,0.001203037,0.00103139,0.0007176091,0.0003175778],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006474371,"about_ca_system_score_gemma":0.0005950085,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004345583,"about_ca_topic_score_gemma":0.005568911,"domain_scores_codex":[0.9993786,0.0001108376,0.00005618625,0.00007954361,0.0002369567,0.0001378437],"domain_scores_gemma":[0.9969397,0.0005723124,0.001457201,0.0001216547,0.0006223918,0.0002868253],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001357487,0.000128968,0.9670616,0.0001550689,0.0001588373,0.0008505423,0.000281503,0.001750831,0.001262649,0.001351968,0.00243093,0.02443125],"study_design_scores_gemma":[0.000009876272,0.0004300288,0.9862462,0.00008231313,0.00008123786,0.0004625064,0.001435771,0.003433301,0.001620287,0.0008948008,0.005279684,0.00002398837],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9795756,0.002123649,0.0006277895,0.001166537,0.0001049387,0.00007615652,0.002309789,0.0000245012,0.01399096],"genre_scores_gemma":[0.996501,0.0009326261,0.0002260971,0.0001433119,0.00009420698,0.0000138116,0.001076793,0.000003344409,0.001008806],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004345583,"threshold_uncertainty_score":0.01139516,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1609106194072367,"score_gpt":0.3134060220491482,"score_spread":0.1524954026419116,"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."}}