{"id":"W2559724803","doi":"10.1021/acschembio.6b00855","title":"High-throughput Identification of DNA-Encoded IgG Ligands that Distinguish Active and Latent<i>Mycobacterium tuberculosis</i>Infections","year":2016,"lang":"en","type":"article","venue":"ACS Chemical Biology","topic":"Tuberculosis Research and Epidemiology","field":"Medicine","cited_by":67,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"NIH Office of the Director; Natural Sciences and Engineering Research Council of Canada; Defense Advanced Research Projects Agency; National Institutes of Health; Bill and Melinda Gates Foundation","keywords":"Epitope; Mycobacterium tuberculosis; Antibody; Antibody Repertoire; Computational biology; Antigen; Biology; Recombinant DNA; DNA sequencing; Epitope mapping; DNA; Tuberculosis; Genetics; Gene; Medicine","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002873628,0.0001836204,0.0005501075,0.00009733738,0.00005780663,0.000006426182,0.0001127844,0.0003475481,0.00008141492],"category_scores_gemma":[0.002524795,0.0001169132,0.0001056418,0.0001578826,0.0006102857,0.00008729925,0.0001552021,0.000209289,0.00003647068],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008641416,"about_ca_system_score_gemma":0.0000440322,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000167092,"about_ca_topic_score_gemma":0.000009783922,"domain_scores_codex":[0.9984052,0.00010095,0.0004618828,0.000494535,0.0001037174,0.0004337434],"domain_scores_gemma":[0.9982931,0.0007669586,0.0001786626,0.0003617996,0.0001899965,0.0002094822],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002010819,0.0001339902,0.1009835,0.0000419942,0.0001561001,0.000002276373,0.00004146845,3.3008e-8,0.8914818,0.0008028376,0.0009562211,0.005198774],"study_design_scores_gemma":[0.001118919,0.0002789689,0.08422146,0.00005198778,0.00009205977,0.00006734333,0.0000161023,0.000005429404,0.9107106,0.002188028,0.001121582,0.000127486],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9903433,0.0001312536,0.0002079972,0.008470289,0.0002121257,0.0002346308,0.0001336149,0.00006283893,0.0002039264],"genre_scores_gemma":[0.9976895,0.001173433,0.0001218224,0.0003691412,0.0002501453,0.00005727063,0.0001934512,0.00001704922,0.0001281694],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01922886,"threshold_uncertainty_score":0.4767582,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02224266621961363,"score_gpt":0.3032868932948234,"score_spread":0.2810442270752098,"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."}}