{"id":"W4293089519","doi":"10.1093/cid/ciac679","title":"The Performance of Computer-Aided Detection Digital Chest X-ray Reading Technologies for Triage of Active Tuberculosis Among Persons With a History of Previous Tuberculosis","year":2022,"lang":"en","type":"article","venue":"Clinical Infectious Diseases","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Institute of Allergy and Infectious Diseases; Government of Canada","keywords":"Medicine; Tuberculosis; Triage; Reading (process); Active tuberculosis; Medical emergency; Mycobacterium tuberculosis; Pathology; Linguistics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.006121568,0.0004322982,0.000286175,0.002154831,0.0001694851,0.0008994285,0.0006631507,0.0006804272,0.0008454549],"category_scores_gemma":[0.01942704,0.0002956818,0.0004749211,0.0007780893,0.0002910935,0.0006058196,0.0005463199,0.0003296929,0.0003885349],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000467601,"about_ca_system_score_gemma":0.0003188341,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001551736,"about_ca_topic_score_gemma":0.002252853,"domain_scores_codex":[0.9958735,0.002189355,0.0004994718,0.0005136518,0.0007621697,0.0001618481],"domain_scores_gemma":[0.9874019,0.007946226,0.002548265,0.0004120127,0.001368907,0.0003226358],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005586983,0.0000801373,0.9882132,0.00005093477,0.00007938364,0.00002272924,0.00007463351,0.0002840241,0.0004179759,0.00002064005,0.0001554833,0.01004202],"study_design_scores_gemma":[0.00009022268,0.001526745,0.9853098,0.0000642349,0.0001948269,0.000488185,0.0001773586,0.009753059,0.001815851,0.0000573189,0.0005024527,0.00001998352],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9960679,0.001328586,0.0008636252,0.00008772076,0.00002516209,0.00004396791,0.0003627111,0.00003192732,0.001188408],"genre_scores_gemma":[0.9979649,0.0001738197,0.001402238,0.00002994391,0.00001434905,0.00002007532,0.0002749851,0.000002427436,0.0001172535],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006121568,"threshold_uncertainty_score":0.03237432,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02693120912796855,"score_gpt":0.3048236146895899,"score_spread":0.2778924055616213,"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."}}