{"id":"W3007183267","doi":"10.1101/2020.02.25.960930","title":"Predicting <i>Vibrio cholerae</i> infection and disease severity using metagenomics in a prospective cohort study","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Vibrio bacteria research studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; McGill Genome Centre; Université de Montréal","funders":"Global Affairs Canada; Department for International Development; International Centre for Diarrhoeal Disease Research, Bangladesh; Styrelsen för Internationellt Utvecklingssamarbete","keywords":"Metagenomics; Vibrio cholerae; Biology; Microbiome; Shotgun sequencing; Prevotella; Disease; Cholera vaccine; Microbiology; DNA sequencing; Computational biology; Gene; Genetics; Medicine; Bacteria; Internal medicine","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":[0.002151367,0.0006416821,0.0005580508,0.000762952,0.0006208573,0.001249194,0.0005917848,0.0008391077,0.0009815375],"category_scores_gemma":[0.002880244,0.0005298675,0.001499837,0.0008000848,0.0002609559,0.0003624235,0.0009626132,0.001221982,0.0002462629],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005164901,"about_ca_system_score_gemma":0.0006451817,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008081745,"about_ca_topic_score_gemma":0.008014629,"domain_scores_codex":[0.9990434,0.0003641021,0.00006296796,0.0003124418,0.00009599351,0.0001210033],"domain_scores_gemma":[0.9983662,0.0004037423,0.0003624582,0.0003620088,0.0002019041,0.0003038725],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004929294,0.00006944359,0.9943772,0.00003173507,0.000838183,0.00008221816,0.0000653103,0.0003212329,0.001579916,0.00004152167,0.0003385931,0.001761655],"study_design_scores_gemma":[0.00004766316,0.0003414302,0.9930457,0.00003941205,0.0007478618,0.0002255259,0.0002917298,0.003809208,0.0006800398,0.000190478,0.0005568391,0.00002406083],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9955956,0.0003965801,0.001399319,0.0001953554,0.00002660171,0.00003161623,0.002106622,0.00002361307,0.0002246966],"genre_scores_gemma":[0.9972029,0.0001609525,0.001227873,0.00009378669,0.00001589998,0.00003071265,0.001130653,0.00001165449,0.000125611],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008081745,"threshold_uncertainty_score":0.01606941,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01590647626901028,"score_gpt":0.2526482212161935,"score_spread":0.2367417449471832,"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."}}