{"id":"W4211016440","doi":"10.1177/08404704211058968","title":"Facing disruption: Learning from the healthcare supply chain responses in British Columbia during the COVID-19 pandemic","year":2022,"lang":"en","type":"article","venue":"Healthcare Management Forum","topic":"Supply Chain Resilience and Risk Management","field":"Business, Management and Accounting","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Canadian Institutes of Health Research","keywords":"Supply chain; Personal protective equipment; Coronavirus disease 2019 (COVID-19); Pandemic; Resilience (materials science); Business; Supply chain management; Health care; Crisis management; Constructive; Psychological resilience; 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Process management; Marketing; Computer science; Medicine; Management; Economics; Process (computing); Economic growth; Psychology; Virology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"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":[0.003922686,0.0005207743,0.0004065642,0.0009150076,0.02389326,0.00911269,0.001992845,0.003113331,0.004023303],"category_scores_gemma":[0.009985451,0.000393657,0.000194245,0.001591682,0.008764039,0.002771748,0.006740701,0.005869864,0.0006865083],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04255978,"about_ca_system_score_gemma":0.06160656,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8051213,"about_ca_topic_score_gemma":0.9325576,"domain_scores_codex":[0.9959843,0.001699736,0.00007282773,0.0002152255,0.0007205753,0.001307356],"domain_scores_gemma":[0.9926186,0.001997537,0.0004020921,0.0001922816,0.001708676,0.003080844],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0001461856,0.0003343992,0.02008552,0.0002235282,0.00001877081,0.005507485,0.87609,0.001176015,0.001378201,0.004135066,0.03839037,0.05251438],"study_design_scores_gemma":[0.000006076827,0.00004817251,0.005554667,0.0001676382,0.000005241701,0.0001418368,0.9566655,0.0002898701,0.0002079331,0.000886284,0.03599628,0.000030548],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9124643,0.0008843926,0.0007865512,0.0421529,0.0002417467,0.0001484166,0.0001334815,0.00005200546,0.04313625],"genre_scores_gemma":[0.9804304,0.00128469,0.0007271261,0.004691048,0.00003766969,0.00003977051,0.00009638558,0.00003708355,0.01265584],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1948787,"threshold_uncertainty_score":0.3920527,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0281972476102579,"score_gpt":0.272172824932356,"score_spread":0.2439755773220981,"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."}}