{"id":"W3210686914","doi":"10.12927/hcq.2021.26618","title":"Leading through Crises: Healthcare Supply Chain Strategies and Lessons Learned from the COVID-19 Challenges","year":2021,"lang":"en","type":"article","venue":"Healthcare Quarterly","topic":"Supply Chain Resilience and Risk Management","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Reach Technologies (Canada); Transport Canada","funders":"","keywords":"Health care; Coronavirus disease 2019 (COVID-19); Pandemic; Public relations; Crisis management; Perspective (graphical); Best practice; Anxiety; Supply chain; Business; Crisis communication; Psychology; Political science; Medicine; Marketing; Computer science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"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":[0.005282354,0.0005313954,0.0002448567,0.001088285,0.005325222,0.008522162,0.001359906,0.0026872,0.004837438],"category_scores_gemma":[0.008409311,0.0002297193,0.0002847595,0.001550234,0.004254298,0.006673381,0.004580967,0.003238637,0.0006114198],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008447899,"about_ca_system_score_gemma":0.01574013,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02983095,"about_ca_topic_score_gemma":0.05967623,"domain_scores_codex":[0.9967493,0.001967561,0.00008750137,0.0001244505,0.0003841352,0.0006870803],"domain_scores_gemma":[0.9943367,0.002692443,0.0003637749,0.0001280959,0.0009738567,0.001505071],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001570425,0.0005003889,0.0179345,0.002071041,0.00005265969,0.005748247,0.3270563,0.004773795,0.00102506,0.1024885,0.113435,0.4247574],"study_design_scores_gemma":[0.00002409818,0.0001866733,0.005744383,0.002751712,0.00002586351,0.001187459,0.7196275,0.002111065,0.0007685657,0.04782377,0.2196786,0.00007037098],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.3002907,0.03612333,0.01305656,0.5437687,0.001940867,0.0003324284,0.0002139616,0.00024108,0.1040324],"genre_scores_gemma":[0.9284762,0.03563467,0.008594156,0.01356631,0.0005204512,0.00009471607,0.0001352381,0.00005202113,0.01292634],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02983095,"threshold_uncertainty_score":0.06129408,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1252595702193104,"score_gpt":0.3567995424178475,"score_spread":0.2315399721985371,"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."}}