{"id":"W3197916146","doi":"10.1016/j.jeca.2021.e00223","title":"Spatial financial contagion during the COVID-19 outbreak: Local correlation approach","year":2021,"lang":"en","type":"article","venue":"The Journal of Economic Asymmetries","topic":"COVID-19 Pandemic Impacts","field":"Economics, Econometrics and Finance","cited_by":28,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"China; Coronavirus disease 2019 (COVID-19); Geography; Contagion effect; Index (typography); Stock (firearms); Financial crisis; Outbreak; Economic geography; Development economics; Economics; Economy; Demographic economics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002797071,0.0002124788,0.000582416,0.0002848482,0.0004296808,0.000129529,0.0005352497,0.0001505189,0.0002693428],"category_scores_gemma":[0.002600809,0.0001615345,0.0002624268,0.0002729511,0.0002836188,0.0004273911,0.0001629915,0.000535314,0.000167792],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001191445,"about_ca_system_score_gemma":0.0007388198,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009608786,"about_ca_topic_score_gemma":0.000272232,"domain_scores_codex":[0.9979359,0.0001384305,0.001263992,0.0002345718,0.00007836767,0.0003487484],"domain_scores_gemma":[0.9968647,0.0009418953,0.001500846,0.0004357588,0.0000720042,0.0001848052],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002660823,0.0004355666,0.4575859,0.0003080369,0.001072083,0.0001117842,0.01529066,0.2235437,0.0001275805,0.2528448,0.03702545,0.00899355],"study_design_scores_gemma":[0.01428423,0.0006856464,0.3566636,0.00008966465,0.0003638183,0.004433221,0.006801101,0.04585768,0.002180016,0.1168912,0.4499215,0.001828362],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5665949,0.0062177,0.4038653,0.01237387,0.00295182,0.0003777225,0.0001570658,0.00003384287,0.007427772],"genre_scores_gemma":[0.9953684,0.0004741522,0.0001256166,0.00245988,0.0007450102,0.000003374458,0.000007388969,0.00002612707,0.0007900319],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4287735,"threshold_uncertainty_score":0.6587185,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03577977756182066,"score_gpt":0.2501877305952708,"score_spread":0.2144079530334501,"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."}}