{"id":"W3144939308","doi":"10.5267/j.uscm.2021.1.007","title":"Supply chain emerging aspects and future directions in the age of COVID-19: A systematic review","year":2021,"lang":"en","type":"review","venue":"Uncertain Supply Chain Management","topic":"Supply Chain Resilience and Risk Management","field":"Business, Management and Accounting","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Supply chain; Resilience (materials science); Supply chain management; Flexibility (engineering); Business; Process management; Analytics; Coronavirus disease 2019 (COVID-19); Risk analysis (engineering); Computer science; Marketing; Data science; 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":["metaepi_narrow"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.004931396,0.001280004,0.00416841,0.002013784,0.0005150532,0.0005587849,0.001927661,0.0002874761,0.0005066511],"category_scores_gemma":[0.0004919575,0.0008753482,0.0009805086,0.00473195,0.0002366572,0.0004440518,0.001153021,0.0007236931,0.00007449553],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004190087,"about_ca_system_score_gemma":0.000157388,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00105268,"about_ca_topic_score_gemma":0.0007097279,"domain_scores_codex":[0.9927877,0.000749727,0.002462482,0.001515266,0.001434662,0.001050221],"domain_scores_gemma":[0.995685,0.0006026744,0.001538884,0.001961981,0.000129669,0.00008181575],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00000444466,0.0002156055,0.00002785228,0.8705536,0.0005303278,0.001271339,0.0004471694,0.00002734841,2.767289e-8,0.04470493,0.01537857,0.06683876],"study_design_scores_gemma":[0.0003786359,0.00001527618,0.00001100525,0.1961512,0.003704662,0.00003240611,0.00602365,0.00008128701,1.310254e-8,0.0005239479,0.7923566,0.0007213866],"study_design_candidate":"systematic_review","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000001754425,0.9744874,0.0001308862,0.006645229,0.0006602431,0.01090129,0.00003390909,0.0001384856,0.007000832],"genre_scores_gemma":[0.00003727125,0.9836858,0.0001428149,0.009091115,0.001006718,0.003742873,0.0009270169,0.0001255665,0.001240825],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.776978,"threshold_uncertainty_score":0.9999952,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02520700640751776,"score_gpt":0.2979545175837883,"score_spread":0.2727475111762706,"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."}}