{"id":"W2477849047","doi":"10.1038/srep30781","title":"Serial testing for latent tuberculosis using QuantiFERON-TB Gold In-Tube: A Markov model","year":2016,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Tuberculosis Research and Epidemiology","field":"Medicine","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; McGill University Health Centre","funders":"Canadian Institutes of Health Research","keywords":"Medicine; Latent tuberculosis; QuantiFERON; Tuberculosis; Cutoff; False positive paradox; Cohort; Incidence (geometry); Internal medicine; Gold standard (test); Population; Mycobacterium tuberculosis; Surgery; Statistics; Pathology; Environmental health","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":[0.002722287,0.001429355,0.002101904,0.0009863244,0.0008270678,0.001635106,0.002746611,0.002164864,0.007451483],"category_scores_gemma":[0.005390104,0.0008697386,0.001587554,0.000700101,0.001539035,0.001235559,0.001390337,0.002107238,0.00081583],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002458208,"about_ca_system_score_gemma":0.002771111,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04856512,"about_ca_topic_score_gemma":0.02317951,"domain_scores_codex":[0.9988789,0.0004616355,0.00003963671,0.0002284046,0.00008332678,0.0003080962],"domain_scores_gemma":[0.9939933,0.004227226,0.0007089009,0.0001553796,0.0004619391,0.0004532772],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003838498,0.0001088628,0.00679616,0.00003735098,0.00009081097,0.0002182505,0.00008465409,0.9720268,0.0004369523,0.01669692,0.001006717,0.002112632],"study_design_scores_gemma":[0.00009739713,0.00005240285,0.0006432396,0.000009812569,0.00004114021,0.0000228494,0.00002536372,0.9957373,0.00006578929,0.003099134,0.0001901717,0.00001530387],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.633722,0.0009966427,0.3424347,0.004202987,0.0002362529,0.0004750907,0.00441442,0.0005894583,0.01292849],"genre_scores_gemma":[0.965029,0.0006170511,0.01536975,0.0004230597,0.0001259502,0.0007386128,0.001641105,0.00005476969,0.01600065],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04856512,"threshold_uncertainty_score":0.09656489,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09733898115726398,"score_gpt":0.3556648421015587,"score_spread":0.2583258609442948,"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."}}