{"id":"W4294433356","doi":"10.1016/j.jclepro.2022.133956","title":"Exploring supply chain sustainability drivers during COVID-19- Tale of 2 cities","year":2022,"lang":"en","type":"article","venue":"Journal of Cleaner Production","topic":"Sustainable Supply Chain Management","field":"Business, Management and Accounting","cited_by":16,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Sustainability; Futures studies; Supply chain; Coronavirus disease 2019 (COVID-19); Flexibility (engineering); Business; Social sustainability; Grounded theory; Comparative case; Sustainability organizations; Pandemic; Qualitative research; Industrial organization; Marketing; Economics; Sociology; Management; Ecology; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002384233,0.00016907,0.0003022155,0.001098007,0.0005808953,0.0000849065,0.0003552306,0.00002106283,0.000458305],"category_scores_gemma":[0.001324864,0.0001764003,0.000171462,0.0007657989,0.0001159675,0.002405624,0.0004448772,0.0003345633,0.000002117001],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001134573,"about_ca_system_score_gemma":0.0001526214,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003409067,"about_ca_topic_score_gemma":0.00001239929,"domain_scores_codex":[0.9978505,0.00008010543,0.0006592572,0.0002768332,0.0008019949,0.0003312862],"domain_scores_gemma":[0.9979911,0.00003679555,0.0009897624,0.0003105204,0.0006391958,0.00003260867],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00156803,0.0006423086,0.1317156,0.005756814,0.0002707879,0.0004481502,0.006004523,0.8181173,0.002025322,0.006574032,0.01732794,0.009549194],"study_design_scores_gemma":[0.002899312,0.0002281262,0.06069337,0.00006736484,0.0002994645,0.0001920229,0.4565417,0.000778029,0.002604478,0.01652082,0.4584673,0.0007080638],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9866247,0.00007473341,0.0002039722,0.01079914,0.001428611,0.0004237441,0.000001313767,0.00005141678,0.0003923752],"genre_scores_gemma":[0.9964524,0.00003088213,0.00007378122,0.0002533371,0.001785695,0.00004024812,0.000005538119,0.00003049801,0.001327653],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8173393,"threshold_uncertainty_score":0.7193394,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03210769146457006,"score_gpt":0.235864882376122,"score_spread":0.203757190911552,"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."}}