{"id":"W2588857516","doi":"10.21037/atm.2017.01.63","title":"The multiple sclerosis microbiome?","year":2017,"lang":"en","type":"letter","venue":"Annals of Translational Medicine","topic":"Gut microbiota and health","field":"Biochemistry, Genetics and Molecular Biology","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Multiple Sclerosis Trust; Multiple Sclerosis Society; Multiple Sclerosis Society of Canada; European Committee for Treatment and Research in Multiple Sclerosis; Canadian Institutes of Health Research; Multiple Sclerosis Scientific Research Foundation; U.S. Department of Veterans Affairs; Teva Pharmaceutical Industries; National Multiple Sclerosis Society; Michael Smith Health Research BC; Biogen","keywords":"Multiple sclerosis; Microbiome; Computational biology; Medicine; Bioinformatics; Biology; Immunology","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":[0.0008484833,0.0004225854,0.0006320347,0.0003287262,0.001199402,0.001484363,0.0005179158,0.007597143,0.006693111],"category_scores_gemma":[0.004560703,0.0001558921,0.0003641439,0.0002407854,0.001260668,0.002432072,0.001136395,0.01059646,0.003862897],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001222953,"about_ca_system_score_gemma":0.0008692788,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001002022,"about_ca_topic_score_gemma":0.00183249,"domain_scores_codex":[0.9994153,0.0002163093,0.00004192671,0.0000779342,0.0001791249,0.00006949125],"domain_scores_gemma":[0.9988592,0.0005200853,0.0001106908,0.00007081835,0.0001761129,0.0002630443],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001502474,0.00006904211,0.003144263,0.0002054303,0.00004620522,0.005142718,0.00024456,0.00007809631,0.001446269,0.009260931,0.8407263,0.139486],"study_design_scores_gemma":[0.0000774083,0.00008686748,0.002301847,0.0007656417,0.00003502701,0.01126643,0.0005905079,0.0002994424,0.0004089506,0.02589965,0.9582437,0.00002459879],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.00159733,0.02291525,0.0003232189,0.9576722,0.01343087,0.000009793307,0.00003891571,0.00005592858,0.003956505],"genre_scores_gemma":[0.03510848,0.03780565,0.0008914733,0.8243339,0.09069774,0.00004304908,0.00007696103,0.00003208531,0.01101065],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.007597143,"threshold_uncertainty_score":0.02239072,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1196417419398712,"score_gpt":0.3375959669897108,"score_spread":0.2179542250498396,"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."}}