{"id":"W4229075275","doi":"10.2196/34363","title":"Examining the Implementation of Digital Health to Strengthen the COVID-19 Pandemic Response and Recovery and Scale up Equitable Vaccine Access in African Countries","year":2022,"lang":"en","type":"preprint","venue":"JMIR Formative Research","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Cancer Institute","keywords":"Pandemic; Preparedness; Global health; International Health Regulations; Public health; Digital health; Business; Environmental health; Economic growth; Health care; Medicine; Political science; Disease; Coronavirus disease 2019 (COVID-19); Infectious disease (medical specialty); Economics; Nursing","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","open_science"],"consensus_categories":[],"category_scores_codex":[0.024161,0.0002492896,0.0006976172,0.0003803866,0.0008916999,0.0002871348,0.0007850367,0.00009077963,0.0001181197],"category_scores_gemma":[0.008933244,0.0001442509,0.0000515525,0.000642086,0.0003350704,0.0003270395,0.009076896,0.001185593,0.000001308654],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00128926,"about_ca_system_score_gemma":0.0007810887,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002148781,"about_ca_topic_score_gemma":0.002191911,"domain_scores_codex":[0.9932498,0.003641414,0.0009748205,0.0004975378,0.0008743823,0.0007619959],"domain_scores_gemma":[0.9608818,0.03778759,0.0004876535,0.0005080975,0.0001689127,0.0001658952],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00544074,0.0001845148,0.5792658,0.00450571,0.000284914,0.000005468795,0.3398009,0.0004149024,0.00001489865,0.00265313,0.04335838,0.02407063],"study_design_scores_gemma":[0.001979197,0.00234615,0.5057598,0.0003523928,0.00002484783,0.00001272778,0.3129707,0.0003551324,0.00001599077,0.1523444,0.02335402,0.0004845932],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9701226,0.0007219113,0.0003346818,0.02486167,0.00005002688,0.002938346,0.0008195604,0.00003277785,0.0001184165],"genre_scores_gemma":[0.996135,0.001368763,0.00006327049,0.0006483335,0.00002661264,0.001593887,0.00002935334,0.00001930645,0.0001154882],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1496913,"threshold_uncertainty_score":0.9994149,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5304002710550965,"score_gpt":0.5830719341394788,"score_spread":0.05267166308438231,"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."}}