{"id":"W3216260787","doi":"10.53092/duiibfd.864146","title":"IMPACT OF PANDEMIC COVID-19’S ON NATIONAL CURRENCY AND FINANCIAL MARKETS: AN ANALYSIS ON DEVELOPING AND DEVELOPED COUNTRIES","year":2021,"lang":"en","type":"article","venue":"Dicle Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi","topic":"COVID-19 Pandemic Impacts","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Developing country; Pandemic; Economics; Currency; Quarter (Canadian coin); China; Coronavirus disease 2019 (COVID-19); International economics; Business; Economy; Geography; Monetary economics; Economic growth","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":[0.0008704272,0.0002449308,0.000299519,0.00112298,0.0002645164,0.0008951008,0.0001941952,0.0003750313,0.001539627],"category_scores_gemma":[0.001879175,0.000124056,0.0009068503,0.001222037,0.0003954257,0.0005649086,0.0006205773,0.0006646889,0.0001259202],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007296444,"about_ca_system_score_gemma":0.0006201155,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01733066,"about_ca_topic_score_gemma":0.009292173,"domain_scores_codex":[0.9997352,0.0000950483,0.00001763762,0.00002292172,0.00003795891,0.00009119921],"domain_scores_gemma":[0.9989399,0.0005055949,0.0002344364,0.00003578834,0.0001640679,0.0001201264],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000654511,0.000403624,0.8999639,0.000211941,0.0004907526,0.003985613,0.0005522442,0.06515186,0.0007269861,0.007361852,0.002765863,0.01773088],"study_design_scores_gemma":[0.00004470735,0.0003637968,0.9472405,0.00007871733,0.0002193838,0.0003983439,0.002709921,0.04289287,0.0006409071,0.001593847,0.003783634,0.00003332599],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9955057,0.0006880898,0.0002339189,0.0002715676,0.000008805868,0.00001736319,0.0003946202,0.000003080627,0.002876898],"genre_scores_gemma":[0.9983619,0.0006569034,0.0001063375,0.00003298964,0.00001121068,0.000007791604,0.0003942827,0.000001248712,0.0004273761],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01733066,"threshold_uncertainty_score":0.03445953,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05468744850860159,"score_gpt":0.3094403107504504,"score_spread":0.2547528622418488,"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."}}