{"id":"W3121438465","doi":"","title":"IMPACT OF CORONA VIRUS COVID-19 ON THE GLOBAL ECONOMY","year":2020,"lang":"en","type":"article","venue":"International Journal of Agricultural and Statistical Sciences","topic":"COVID-19 Pandemic Impacts","field":"Economics, Econometrics and Finance","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Recession; Business; Coronavirus disease 2019 (COVID-19); Agriculture; Economic impact analysis; Economic sector; Global recession; World economy; Quarter (Canadian coin); Outbreak; Pandemic; Economy; Government (linguistics); Economic growth; Economic policy; Economics; Geography; Infectious disease (medical specialty); Political science","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":[0.000455854,0.0001858754,0.0001710431,0.0006674589,0.0002806866,0.001121351,0.00009800759,0.0003926271,0.00316993],"category_scores_gemma":[0.001699081,0.00004651368,0.0002739535,0.0008280543,0.0002959876,0.000799079,0.0006451537,0.0006200389,0.0001975356],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001109923,"about_ca_system_score_gemma":0.0007895582,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00708034,"about_ca_topic_score_gemma":0.006850036,"domain_scores_codex":[0.9997218,0.00009023347,0.000009976448,0.00002686765,0.0000688587,0.0000822118],"domain_scores_gemma":[0.9994159,0.00021798,0.0001425606,0.00001988135,0.0001415951,0.00006217206],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004411213,0.0002690713,0.5431201,0.001068143,0.0003551897,0.006777912,0.0009128931,0.03845272,0.003002416,0.1393767,0.06953159,0.1966921],"study_design_scores_gemma":[0.00003202612,0.000577771,0.6298808,0.001083538,0.0002528998,0.00275036,0.007820247,0.030381,0.003085845,0.07655989,0.2474716,0.0001040443],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7638513,0.05214433,0.003812611,0.04687263,0.001316875,0.0000597337,0.0040962,0.00005680137,0.1277895],"genre_scores_gemma":[0.9761579,0.01709719,0.0004190414,0.001161182,0.0003374124,0.00001004041,0.0005815572,0.00001128606,0.004224396],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00708034,"threshold_uncertainty_score":0.01407826,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08277742588055635,"score_gpt":0.3373621528652903,"score_spread":0.2545847269847339,"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."}}