{"id":"W4401235411","doi":"10.1186/s44263-024-00081-2","title":"Expanding molecular diagnostic coverage for tuberculosis by combining computer-aided chest radiography and sputum specimen pooling: a modeling study from four high-burden countries","year":2024,"lang":"en","type":"article","venue":"BMC Global and Public Health","topic":"Tuberculosis Research and Epidemiology","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Foreign, Commonwealth and Development Office; Medical Research Council; Global Affairs Canada; Department of Health and Social Care; Wellcome Trust","keywords":"Medicine; Pooling; Tuberculosis; Baseline (sea); Sputum; Case finding; Artificial intelligence; Computer science; Pathology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001503089,0.0003129045,0.0008847681,0.0002099196,0.000324595,0.0003316216,0.0001118814,0.0001376003,0.00001543178],"category_scores_gemma":[0.0006411824,0.000267934,0.0001350514,0.0003883835,0.00009752627,0.0002023908,0.0001413948,0.0002767261,0.000003597585],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002283493,"about_ca_system_score_gemma":0.0004035285,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01034532,"about_ca_topic_score_gemma":0.000150709,"domain_scores_codex":[0.9969249,0.0003598167,0.0006304745,0.0007788764,0.0003633347,0.0009426436],"domain_scores_gemma":[0.9973984,0.001241194,0.00007768689,0.0002477853,0.0001013962,0.0009335139],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006815085,0.001070434,0.8870722,0.003994244,0.002936472,0.0004033748,0.003178053,0.0008215678,0.0002285657,0.011228,0.04226584,0.04611974],"study_design_scores_gemma":[0.01490234,0.008021532,0.1998864,0.001673552,0.0006016166,0.0003788303,0.004229838,0.7330103,0.00001668744,0.01092659,0.02501776,0.001334521],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8948798,0.01499742,0.07103816,0.01668843,0.0002495624,0.001400097,0.0005424488,0.0001444238,0.00005971435],"genre_scores_gemma":[0.9912865,0.003097904,0.002614496,0.002003505,0.0004868831,0.0001131762,0.000358571,0.00003134947,0.00000758517],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7321887,"threshold_uncertainty_score":0.9999773,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0465216838004214,"score_gpt":0.3380795572061123,"score_spread":0.2915578734056909,"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."}}