{"id":"W3137697531","doi":"10.1016/s2666-5247(21)00057-4","title":"Learning from COVID-19 to reimagine tuberculosis diagnosis","year":2021,"lang":"en","type":"article","venue":"The Lancet Microbe","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Syndemic; Tuberculosis; Pandemic; Medicine; Leverage (statistics); Coronavirus disease 2019 (COVID-19); Environmental health; Public health; Infectious disease (medical specialty); Nursing; Computer science","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0004511499,0.0002361675,0.000599581,0.000089424,0.0002390678,0.00009708087,0.0002970863,0.00009096753,0.00200783],"category_scores_gemma":[0.003565107,0.0001872108,0.0001697361,0.0006286979,0.00008070863,0.0000552286,0.0003910601,0.0005547415,0.0008178394],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003832519,"about_ca_system_score_gemma":0.0003828235,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002015703,"about_ca_topic_score_gemma":0.0003061861,"domain_scores_codex":[0.9981291,0.0002371432,0.0002860796,0.0005735648,0.0002777028,0.0004963903],"domain_scores_gemma":[0.997025,0.001386506,0.00007529326,0.001004159,0.000141233,0.0003678385],"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":[0.0001572122,0.0002114087,0.1175047,0.0001486621,0.0002259569,0.000414635,0.002716735,0.0009028994,0.09388461,0.00006109135,0.7781519,0.00562024],"study_design_scores_gemma":[0.001496811,0.00007519322,0.02026947,0.0002607858,0.0002622681,0.00006998981,0.0002211474,0.00009571967,0.04566291,0.0001707315,0.9311819,0.0002330477],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.3742852,0.001945356,0.0004632688,0.6220213,0.000255977,0.0003009221,0.0000534222,0.0002822221,0.0003922814],"genre_scores_gemma":[0.3718544,0.001669638,0.004046966,0.6183635,0.001743231,0.0001715941,0.0001946902,0.00008604713,0.001869954],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.1530301,"threshold_uncertainty_score":0.9999601,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05330673296378879,"score_gpt":0.3381015753043581,"score_spread":0.2847948423405693,"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."}}