{"id":"W4328094380","doi":"10.54691/bcpbm.v38i.3960","title":"China’s Supply Chain During COVID-19: Disruption and Mitigation","year":2023,"lang":"en","type":"article","venue":"BCP Business & Management","topic":"Supply Chain Resilience and Risk Management","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Supply chain; Business; China; Damages; Coronavirus disease 2019 (COVID-19); Quarantine; Resilience (materials science); Robustness (evolution); Industrial organization; Marketing","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008134139,0.000416454,0.0002025475,0.00124519,0.001878844,0.002026499,0.0005800243,0.0008997036,0.002969578],"category_scores_gemma":[0.001393058,0.000220724,0.0004321309,0.002032143,0.0007402703,0.001600835,0.002074295,0.000466341,0.0003689693],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004496241,"about_ca_system_score_gemma":0.005889535,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07660823,"about_ca_topic_score_gemma":0.06135162,"domain_scores_codex":[0.9993648,0.00007922758,0.00004527056,0.00007586071,0.0002521266,0.0001828298],"domain_scores_gemma":[0.998956,0.0000790444,0.0003301089,0.00008145157,0.000398454,0.0001549653],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006414694,0.0002172336,0.5262134,0.0007431048,0.0003172649,0.008653983,0.009847737,0.1352472,0.02051936,0.05266233,0.03277768,0.2121593],"study_design_scores_gemma":[0.00006863107,0.0006843046,0.6275591,0.0004986385,0.0003484469,0.001168758,0.01669112,0.1781561,0.01332579,0.03098712,0.1302221,0.0002899336],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.952803,0.001193144,0.01258771,0.004977248,0.0001405866,0.0002237116,0.001007757,0.0002393307,0.02682756],"genre_scores_gemma":[0.9937563,0.0004948041,0.0011639,0.0001315814,0.00001748128,0.00002536182,0.000426565,0.000009806776,0.0039742],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07660823,"threshold_uncertainty_score":0.1523247,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01173834620510394,"score_gpt":0.2466296558691724,"score_spread":0.2348913096640685,"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."}}