{"id":"W2940680184","doi":"10.1101/616656","title":"An <i>in vitro</i> model maintaining taxon-specific functional activities of the gut microbiome","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gut microbiota and health","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Institute for Advanced Research; University of Toronto; University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; Ministero dello Sviluppo Economico; Government of Canada; Canadian Institutes of Health Research; Genome Canada; Ontario Genomics; Ontario Ministry of Economic Development and Innovation; Ontario Genomics Institute","keywords":"Microbiome; Biology; Gut microbiome; In vivo; Computational biology; In vitro; Taxon; Bioinformatics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007998694,0.0008280701,0.0006118536,0.0004942557,0.0003870748,0.0009698606,0.0006415164,0.0007653834,0.001235086],"category_scores_gemma":[0.0005901128,0.00037512,0.0007975951,0.0004766515,0.0004544482,0.0005635193,0.000839762,0.00114258,0.0008451866],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004973924,"about_ca_system_score_gemma":0.0003833663,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001697981,"about_ca_topic_score_gemma":0.001346204,"domain_scores_codex":[0.9992887,0.0001439848,0.00005627579,0.0001837605,0.0002396599,0.00008760549],"domain_scores_gemma":[0.999209,0.0001625887,0.000218612,0.0002113887,0.000113931,0.00008458722],"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":[0.000113218,0.00006804807,0.0009420579,0.00007009815,0.00001585472,0.00005642889,0.00002391376,0.002608528,0.9937186,0.0003359785,0.0002634012,0.001783734],"study_design_scores_gemma":[0.00001061735,0.0003538001,0.00362297,0.00001568308,0.00003524993,0.0001649724,0.00004518667,0.02257596,0.9689753,0.0002747846,0.003899812,0.00002568603],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7427514,0.001394323,0.2355259,0.0006820065,0.0002937541,0.0002863012,0.008842051,0.002230018,0.007994212],"genre_scores_gemma":[0.8941233,0.001038795,0.0928779,0.0003016966,0.00005219464,0.000431087,0.006293889,0.0003314031,0.004549661],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001697981,"threshold_uncertainty_score":0.004230142,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01360518803253613,"score_gpt":0.2167568643706091,"score_spread":0.203151676338073,"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."}}