{"id":"W4210250080","doi":"10.1016/s1473-3099(22)00028-7","title":"COVID-19 vaccine inequity, dependency, and production capability in low-income and middle-income countries: the case of Bangladesh","year":2022,"lang":"en","type":"article","venue":"The Lancet Infectious Diseases","topic":"Vaccine Coverage and Hesitancy","field":"Social Sciences","cited_by":19,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"Research Nova Scotia; Genome Canada; Dalhousie Medical Research Foundation; Canadian Institutes of Health Research; Li Ka Shing Foundation","keywords":"Vaccination; Government (linguistics); Public health; Population; Global health; Developing country; Workforce","routes":{"ca_aff":true,"ca_fund":true,"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":["sts"],"consensus_categories":[],"category_scores_codex":[0.00152838,0.0001205226,0.0002812424,0.00007598457,0.001354429,0.00006484934,0.0002183822,0.00003305778,0.0002898045],"category_scores_gemma":[0.001513488,0.00008378469,0.00004307752,0.0004504817,0.0001188337,0.0001987865,0.0002563185,0.0002110621,0.000001249717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002662426,"about_ca_system_score_gemma":0.0003495476,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01207558,"about_ca_topic_score_gemma":0.04764973,"domain_scores_codex":[0.9982634,0.0007134003,0.0002506699,0.0002652505,0.0002329369,0.0002742992],"domain_scores_gemma":[0.9986662,0.0006297576,0.0001479924,0.0003572334,0.00006352102,0.0001353196],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001158938,0.00009528224,0.9879729,0.0003327402,0.00002046075,0.00008860877,0.007001706,0.0001684283,0.000002749109,0.003758847,0.0001948993,0.0002475325],"study_design_scores_gemma":[0.001950267,0.0002304292,0.9255258,0.00008538456,0.000150462,0.0004676987,0.00795179,0.0000774498,0.00001256638,0.06049922,0.002745176,0.0003036835],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9877234,0.002319159,0.000004931029,0.008597392,0.0002141873,0.0006435427,0.0001038298,0.00008030068,0.0003132747],"genre_scores_gemma":[0.9979835,0.0008729949,0.000001601621,0.0006275566,0.0003343395,0.0001120568,0.000003507923,0.000008590518,0.00005591791],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06244698,"threshold_uncertainty_score":0.9999457,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0228370282684193,"score_gpt":0.3048894465233787,"score_spread":0.2820524182549594,"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."}}