{"id":"W3129065090","doi":"10.1186/s40168-020-00992-w","title":"Accurate identification and quantification of commensal microbiota bound by host immunoglobulins","year":2021,"lang":"en","type":"article","venue":"Microbiome","topic":"Gut microbiota and health","field":"Biochemistry, Genetics and Molecular Biology","cited_by":69,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre; University of British Columbia","funders":"National Eye Institute; Berlin Institute of Health; Deutsche Forschungsgemeinschaft; Marie Curie; Mayo Clinic; Versus Arthritis; Kennedy Trust for Rheumatology Research; Volkswagen Foundation; Linacre College, University of Oxford; Cleveland Clinic; Wellcome Trust; Canadian Institutes of Health Research; Wellcome; European Molecular Biology Organization","keywords":"Biology; Antibody; Microbiome; Computational biology; Antibody Repertoire; Identification (biology); Host (biology); Taxon; Evolutionary biology; Immunology; Genetics; Ecology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001877442,0.0001452416,0.0001739399,0.00004442268,0.0001216939,0.00006101156,0.0001397559,0.0001654551,0.00002354307],"category_scores_gemma":[0.00002415489,0.0001597048,0.00005817265,0.0001594774,0.0001491994,0.000007007166,0.0001121789,0.00007435973,0.0000219281],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001996551,"about_ca_system_score_gemma":0.0001071516,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005182226,"about_ca_topic_score_gemma":0.00003250568,"domain_scores_codex":[0.9988992,0.00007686668,0.0003740195,0.0003928833,0.00004242303,0.0002146595],"domain_scores_gemma":[0.9991356,0.000009540345,0.0001895427,0.0004301314,0.0001825784,0.00005267611],"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":[0.00002717927,0.0001145535,0.0003707922,0.00007265868,0.00003957903,8.233763e-7,0.00005850805,3.797957e-7,0.9796818,0.00004579145,0.01939367,0.0001942347],"study_design_scores_gemma":[0.0004446674,0.00004985466,0.01096121,0.00001951475,0.00001941318,0.00006230214,0.00008257188,0.000003963532,0.9123399,0.000005094038,0.07585736,0.0001541415],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9919525,0.004653428,0.001401836,0.001042702,0.0001904858,0.000157117,0.0005441773,0.000009767523,0.00004801884],"genre_scores_gemma":[0.9941871,0.0009050676,0.0003992909,0.0003035237,0.00003614993,0.000004518864,0.002679765,0.00002090111,0.001463689],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06734192,"threshold_uncertainty_score":0.6512571,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01132272327350467,"score_gpt":0.2702673287999427,"score_spread":0.2589446055264381,"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."}}