{"id":"W4389484282","doi":"10.5588/pha.23.0044","title":"Lessons for TB from the COVID-19 response: qualitative data from Brazil, India and South Africa","year":2023,"lang":"en","type":"article","venue":"Public Health Action","topic":"Tuberculosis Research and Epidemiology","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"African Union Commission; African Union; African Academy of Sciences; European Commission; Ministério da Ciência, Tecnologia e Inovação; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Department of Science and Technology, Ministry of Science and Technology, India; Medical Research Council; South African Medical Research Council; National Research Foundation","keywords":"Pandemic; Economic growth; Medicine; Public health; Qualitative research; Developing country; Politics; Coronavirus disease 2019 (COVID-19); Environmental health; Political science; Public relations; Nursing; Sociology; Social science; Disease; Economics","routes":{"ca_aff":true,"ca_fund":false,"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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.009818924,0.0001135873,0.0003282282,0.0001755032,0.0004644,0.00005002513,0.0002252416,0.0001300143,0.0001146852],"category_scores_gemma":[0.04399154,0.00007867271,0.00003806837,0.000456375,0.0001332797,0.0002153187,0.0001658903,0.0003628595,0.0001017156],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002645101,"about_ca_system_score_gemma":0.001850773,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005941185,"about_ca_topic_score_gemma":0.0008416704,"domain_scores_codex":[0.9957356,0.00249288,0.0003459076,0.0005149163,0.0002663218,0.0006443087],"domain_scores_gemma":[0.9839882,0.01415951,0.0001588068,0.0006932784,0.0000770023,0.0009232166],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001804328,0.00005415456,0.005544781,0.0000863383,0.0001448229,0.000003294933,0.04338614,6.810221e-7,0.00019603,0.0003804439,0.9313151,0.01708387],"study_design_scores_gemma":[0.001169929,0.0002239298,0.2234015,0.00001220321,0.00001442225,0.000003004757,0.01953045,0.001286083,0.00000242228,0.001703482,0.7525858,0.00006678917],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.184193,0.0005976718,0.003826163,0.8057415,0.0001814704,0.0007774007,0.004501501,0.0001384062,0.0000428216],"genre_scores_gemma":[0.9395287,0.0008737811,0.0008498791,0.04886612,0.0006985621,0.0002923094,0.008441249,0.00003162715,0.0004177788],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7568755,"threshold_uncertainty_score":0.9640613,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6392133059233185,"score_gpt":0.5893739908181808,"score_spread":0.04983931510513773,"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."}}