{"id":"W2129742737","doi":"10.1371/journal.pbio.1002050","title":"Where Next for Microbiome Research?","year":2015,"lang":"en","type":"article","venue":"PLoS Biology","topic":"Gut microbiota and health","field":"Biochemistry, Genetics and Molecular Biology","cited_by":168,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre; University of British Columbia","funders":"National Center for Complementary and Integrative Health; National Institute of Allergy and Infectious Diseases","keywords":"Biology; Metagenomics; Microbiome; Computational biology; DNA sequencing; Data science; Profiling (computer programming); Evolutionary biology; Bioinformatics; Genetics; DNA; Computer science; Gene","routes":{"ca_aff":true,"ca_fund":false,"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":[0.02562359,0.001518763,0.00300069,0.00227036,0.00595211,0.01646564,0.003222757,0.01103503,0.02746896],"category_scores_gemma":[0.02847736,0.0007540244,0.001701925,0.001898755,0.01463564,0.04856122,0.008789601,0.02282114,0.01216635],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003943947,"about_ca_system_score_gemma":0.01868143,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004299919,"about_ca_topic_score_gemma":0.008890549,"domain_scores_codex":[0.9899818,0.005355643,0.0005724842,0.001308694,0.001638371,0.001142903],"domain_scores_gemma":[0.9746381,0.01020453,0.001154269,0.002266588,0.004871621,0.006864783],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002725267,0.0001847499,0.001640572,0.00306615,0.0001774096,0.0006443192,0.002292263,0.0002291625,0.001567748,0.15355,0.6380775,0.1982975],"study_design_scores_gemma":[0.00002481097,0.00006752823,0.0006154185,0.002368606,0.00004998388,0.0003277202,0.005671423,0.0001166649,0.0002402949,0.2138607,0.7765837,0.00007313411],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0004675348,0.1500946,0.00419866,0.8073,0.03377194,0.00002696655,0.0001281285,0.0001928182,0.003819296],"genre_scores_gemma":[0.03553842,0.3593025,0.04066741,0.4806659,0.05840254,0.0003856492,0.0006312912,0.0005023372,0.02390399],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.02746896,"threshold_uncertainty_score":0.1355121,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1809367645471026,"score_gpt":0.3997268681279392,"score_spread":0.2187901035808365,"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."}}