{"id":"W2340846200","doi":"10.1371/journal.pone.0154032","title":"Chest Radiographic Patterns and the Transmission of Tuberculosis: Implications for Automated Systems","year":2016,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Tuberculosis Research and Epidemiology","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Health Services; Provincial Laboratory of Public Health; University of Alberta","funders":"University of Alberta; Alberta Health Services","keywords":"Medicine; Tuberculosis; Chest radiograph; Radiography; Transmission (telecommunications); Odds ratio; Confidence interval; Pulmonary tuberculosis; Mycobacterium tuberculosis; Lung; Radiology; Airborne transmission; Young adult; Internal medicine; Surgery; Pathology; Disease; Coronavirus disease 2019 (COVID-19); Infectious disease (medical specialty)","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.005699837,0.0003709582,0.000317069,0.001994032,0.0004576092,0.00304669,0.001069721,0.001087686,0.003438388],"category_scores_gemma":[0.06375298,0.0002536108,0.0002651886,0.001888908,0.00119533,0.001805894,0.0006055711,0.0005762036,0.0006117678],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002011392,"about_ca_system_score_gemma":0.002585082,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02151956,"about_ca_topic_score_gemma":0.01298401,"domain_scores_codex":[0.9959255,0.002277587,0.0002539009,0.0002244528,0.001154304,0.0001640898],"domain_scores_gemma":[0.9530421,0.02688418,0.009428895,0.001807912,0.007346085,0.00149079],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003032401,0.0001182676,0.8834449,0.0001357645,0.00004764182,0.0001756509,0.0002302311,0.00228026,0.0002525673,0.001268367,0.002666578,0.1090765],"study_design_scores_gemma":[0.00007159731,0.0005023863,0.950811,0.0005400443,0.000112542,0.001457902,0.001804895,0.03487495,0.0004721374,0.00399829,0.005310687,0.00004359265],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8841643,0.02368111,0.01782612,0.05080121,0.0003979674,0.0003432711,0.001378329,0.000600065,0.02080766],"genre_scores_gemma":[0.9907674,0.002745297,0.004959066,0.0004804689,0.0001837577,0.00004407594,0.000166205,0.00001652753,0.0006370835],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02151956,"threshold_uncertainty_score":0.04278862,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0542859214519907,"score_gpt":0.303682084170158,"score_spread":0.2493961627181673,"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."}}