{"id":"W3202350924","doi":"10.3390/jrfm14100461","title":"Propagation of International Supply-Chain Disruptions between Firms in a Country","year":2021,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Global trade and economics","field":"Economics, Econometrics and Finance","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Japan Society for the Promotion of Science; Research Institute of Economy, Trade and Industry","keywords":"Supply chain; Shock (circulatory); China; Supply shock; Monetary economics; Exchange rate; International economics; Economics; Business; Econometrics; Industrial organization; Monetary policy","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":[0.0008776832,0.0004529408,0.0003203471,0.0009764782,0.0003692509,0.001217221,0.0004677974,0.0006310747,0.001630386],"category_scores_gemma":[0.005904947,0.0004241061,0.0005542455,0.001621045,0.000551814,0.001905166,0.0008003352,0.0009030887,0.0001794053],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001263065,"about_ca_system_score_gemma":0.0004257204,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02611778,"about_ca_topic_score_gemma":0.01717529,"domain_scores_codex":[0.99965,0.00009864613,0.00002729161,0.00009953262,0.0000553796,0.00006912285],"domain_scores_gemma":[0.9977494,0.0009374922,0.0006678129,0.0002680525,0.0002372437,0.0001399742],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001816448,0.00007449024,0.1735978,0.00004040817,0.0001606625,0.0002993554,0.0003280296,0.8099679,0.0008817816,0.004160884,0.0007681605,0.009538843],"study_design_scores_gemma":[0.00002580086,0.0001220189,0.0669323,0.00002137798,0.00009465271,0.0001115819,0.0006578389,0.9240387,0.001592138,0.004929056,0.001427207,0.00004738785],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9917805,0.00007395872,0.006496995,0.0001032841,0.000008265414,0.0000157073,0.000474178,0.00006480756,0.0009823758],"genre_scores_gemma":[0.9980787,0.00008098913,0.001058804,0.00001140672,0.000001982039,0.000008525135,0.0004418077,0.000005759314,0.0003119321],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02611778,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01905602028189261,"score_gpt":0.212392680056688,"score_spread":0.1933366597747954,"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."}}