{"id":"W2992949780","doi":"10.1097/olq.0000000000001107","title":"Highlights From the 2019 HIV Diagnostics Conference: Optimizing Testing for HIV, STIs, and HCV","year":2019,"lang":"en","type":"article","venue":"Sexually Transmitted Diseases","topic":"HIV/AIDS Research and Interventions","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institutes of Health","keywords":"Medicine; Human immunodeficiency virus (HIV); Session (web analytics); Atlanta; Men who have sex with men; Disease control; Hepatitis C; Best practice; Food and drug administration; Family medicine; Medical education; Virology; Medical emergency; Political science; Pathology; World Wide Web","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001075865,0.0002132342,0.00032145,0.00007261407,0.0001994062,0.0001209584,0.0001959836,0.00007658052,0.000524788],"category_scores_gemma":[0.0008553626,0.000145098,0.0001280999,0.0001624702,0.0001486064,0.0001545436,0.00003715799,0.0002001817,0.0001004464],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002332849,"about_ca_system_score_gemma":0.0002412002,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001551594,"about_ca_topic_score_gemma":0.00003126691,"domain_scores_codex":[0.9984612,0.00008114291,0.0003085088,0.0003965924,0.0003340224,0.0004185727],"domain_scores_gemma":[0.9966455,0.002305459,0.0000597913,0.0003570263,0.0002701764,0.0003620819],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.001787621,0.002050427,0.379433,0.001280424,0.001444004,0.0001368643,0.002798629,0.00007062458,0.01458146,0.006410104,0.4992951,0.09071167],"study_design_scores_gemma":[0.02715063,0.0117008,0.7569349,0.005807126,0.003598632,0.00004120869,0.005959994,0.05258778,0.002234114,0.005750434,0.1263967,0.0018377],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9341353,0.01255565,0.02348581,0.01419879,0.0002115337,0.003305201,0.008305644,0.0003002296,0.003501846],"genre_scores_gemma":[0.9792582,0.0007376382,0.005528567,0.0006443413,0.0003941373,0.0001507209,0.002019659,0.00006347293,0.01120328],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3775018,"threshold_uncertainty_score":0.5916927,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02629795384045668,"score_gpt":0.2954989776507385,"score_spread":0.2692010238102818,"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."}}