{"id":"W3094243067","doi":"10.1016/j.hjdsi.2020.100487","title":"Commentary: Lessons from the COVID-19 global health response to inform TB case finding","year":2020,"lang":"en","type":"article","venue":"Healthcare","topic":"Tuberculosis Research and Epidemiology","field":"Medicine","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; McGill University Health Centre; Université de Montréal","funders":"","keywords":"Pandemic; Coronavirus disease 2019 (COVID-19); Death toll; Toll; Public health; Disease; Tuberculosis; Infectious disease (medical specialty); Global health; Economic growth; Development economics; Action (physics); Medicine; Environmental health; Political science; Immunology; Economics; Nursing","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01585635,0.001214094,0.002439536,0.002026748,0.004959312,0.005681932,0.008150858,0.07217524,0.01323323],"category_scores_gemma":[0.1780218,0.001157903,0.002384592,0.00174262,0.007735896,0.01120328,0.003638779,0.06326374,0.008434218],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006614966,"about_ca_system_score_gemma":0.01190953,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01030719,"about_ca_topic_score_gemma":0.01241281,"domain_scores_codex":[0.9867508,0.006151913,0.001725649,0.001486309,0.002980125,0.0009052515],"domain_scores_gemma":[0.8407144,0.1204117,0.005321442,0.00236899,0.02131893,0.009864587],"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":[0.00002112645,0.000008822972,0.00009865501,0.0001377832,0.00001246363,0.0002996167,0.0001272995,0.00003483794,0.00002669569,0.0008767407,0.9945592,0.003796724],"study_design_scores_gemma":[0.0001606914,0.00006459255,0.0006871446,0.002833387,0.00008796759,0.001833008,0.001114505,0.0004061084,0.0002011565,0.01121931,0.9812419,0.000150235],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0000638154,0.001470477,0.00008270054,0.950225,0.04748607,0.00001022566,0.00005377748,0.00002263863,0.0005852968],"genre_scores_gemma":[0.001364064,0.001728775,0.0001738645,0.8940037,0.1016885,0.00002270147,0.00003534772,0.00002331761,0.0009598751],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.07217524,"threshold_uncertainty_score":0.08385736,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.22840016179317,"score_gpt":0.5145799916062433,"score_spread":0.2861798298130733,"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."}}