{"id":"W2615068833","doi":"10.1183/13993003.02159-2016","title":"An evaluation of automated chest radiography reading software for tuberculosis screening among public- and private-sector patients","year":2017,"lang":"en","type":"article","venue":"European Respiratory Journal","topic":"Tuberculosis Research and Epidemiology","field":"Medicine","cited_by":71,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Unitaid; Global Affairs Canada; Government of Canada","keywords":"Medicine; Receiver operating characteristic; Triage; Tuberculosis; Grading (engineering); Radiography; Prospective cohort study; Diagnostic accuracy; Radiology; Emergency medicine; Surgery; Internal medicine; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006829144,0.0003930097,0.000415474,0.001366178,0.000278976,0.0008891108,0.0005256695,0.0007323973,0.001184667],"category_scores_gemma":[0.03262661,0.0002646077,0.0006877987,0.001190044,0.0003683496,0.001031444,0.0005132983,0.0003476476,0.0004019453],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000618834,"about_ca_system_score_gemma":0.000424586,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00189713,"about_ca_topic_score_gemma":0.002771108,"domain_scores_codex":[0.9935454,0.002956752,0.0008141699,0.0005508024,0.001858129,0.0002748079],"domain_scores_gemma":[0.9735399,0.01393583,0.005975076,0.001048236,0.004708011,0.0007929763],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001213334,0.0002509092,0.9858335,0.00009008324,0.0001285092,0.00006144461,0.0003008166,0.0002018917,0.0003281576,0.00002266141,0.0001486253,0.01142007],"study_design_scores_gemma":[0.00005562975,0.003331357,0.9923189,0.00002576854,0.0001257259,0.0002710429,0.0003389471,0.002793023,0.0003584327,0.00002267085,0.0003407048,0.00001790467],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988231,0.0002419466,0.0001573908,0.00003477705,0.000006162704,0.00004605094,0.0001306159,0.00001020383,0.0005496424],"genre_scores_gemma":[0.9994007,0.00006374557,0.0002959424,0.0000164754,0.000006855229,0.00002190469,0.0001045897,0.000002280442,0.00008743811],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006829144,"threshold_uncertainty_score":0.03611636,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0970723077831332,"score_gpt":0.3627925521485918,"score_spread":0.2657202443654586,"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."}}