{"id":"W3110330849","doi":"10.1080/02255189.2020.1857225","title":"Commodity exporter’s vulnerabilities in times of COVID-19: the case of Ghana","year":2021,"lang":"fr","type":"article","venue":"Canadian Journal of Development Studies/Revue canadienne d études du développement","topic":"Supply Chain Resilience and Risk Management","field":"Business, Management and Accounting","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Commodity; Supply chain; Coronavirus disease 2019 (COVID-19); Resilience (materials science); Business; Commodity chain; Psychological resilience; 2019-20 coronavirus outbreak; Financial crisis; Economics; Commerce; International economics; Industrial organization; Production (economics); Finance; Microeconomics; Macroeconomics; Marketing; Virology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008127154,0.0002621693,0.0002490672,0.0005645803,0.005358626,0.002376368,0.0005731018,0.002340812,0.006049836],"category_scores_gemma":[0.001923544,0.0002327137,0.0001677972,0.00143927,0.005484908,0.003290878,0.003564776,0.002139506,0.0002735698],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005205028,"about_ca_system_score_gemma":0.002729885,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07820474,"about_ca_topic_score_gemma":0.1214326,"domain_scores_codex":[0.999522,0.0001913525,0.0000118561,0.00002592798,0.00002572346,0.0002231082],"domain_scores_gemma":[0.9991142,0.0003551659,0.0002307153,0.00003614881,0.00005779705,0.0002059905],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.000303083,0.0001900558,0.09712265,0.0003718582,0.00003985408,0.1558431,0.5035022,0.002762555,0.002589308,0.195205,0.01295245,0.02911779],"study_design_scores_gemma":[0.00003534207,0.00007586401,0.03718231,0.0005881956,0.00002699034,0.007050211,0.8640362,0.001706437,0.000465402,0.02504897,0.06374097,0.00004299402],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9600195,0.0008084547,0.0004865612,0.01538007,0.00003157365,0.00002847911,0.00006770289,0.000008211836,0.02316945],"genre_scores_gemma":[0.9963342,0.0006745064,0.0002533072,0.0005366171,0.000008354981,0.000009960124,0.00001645613,0.000006144183,0.002160518],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07820474,"threshold_uncertainty_score":0.1554991,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05559628409062693,"score_gpt":0.2627604573932905,"score_spread":0.2071641733026635,"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."}}