{"id":"W2566431041","doi":"10.1016/j.msard.2016.12.007","title":"From bugs to brains: The microbiome in neurological health","year":2016,"lang":"en","type":"editorial","venue":"Multiple Sclerosis and Related Disorders","topic":"Gut microbiota and health","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre; Simon Fraser University; University of British Columbia","funders":"Health Canada; University of British Columbia; Canada Research Chairs","keywords":"Microbiome; Gut microbiome; Multiple sclerosis; Medicine; Discipline; Engineering ethics; Neuroscience; Data science; Bioinformatics; Biology; Sociology; Immunology; Computer science; Social science; Engineering","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":[0.0003736052,0.000382335,0.0004348468,0.0001001879,0.0002264581,0.00005276699,0.0003875819,0.001212453,0.00002871509],"category_scores_gemma":[0.000337295,0.0002416663,0.0001427969,0.0001637503,0.0001821173,0.000003625905,0.0002991056,0.0006234521,0.00003775977],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002764393,"about_ca_system_score_gemma":0.0002165984,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001611858,"about_ca_topic_score_gemma":0.002500136,"domain_scores_codex":[0.9975337,0.0002686077,0.0005152542,0.0009267228,0.0001595354,0.0005962087],"domain_scores_gemma":[0.9988857,0.0001973633,0.0001910341,0.0004875233,0.00004324279,0.0001951552],"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":[0.0001755794,0.0001055956,0.0007343465,0.00002783717,0.0000628212,8.860727e-7,0.0003317893,0.000008378683,0.07118586,0.000001792992,0.917712,0.009653155],"study_design_scores_gemma":[0.002254578,0.0004431825,0.01410976,0.0002019172,0.00001401589,8.112695e-7,0.00007343167,0.000007678075,0.0001048735,0.00005556455,0.9823568,0.0003773295],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.494931,0.01629728,0.0000625776,0.02765494,0.456091,0.002138777,0.002553344,0.00007049483,0.0002006077],"genre_scores_gemma":[0.5652034,0.0948383,0.000428557,0.008329291,0.3207509,0.0002872014,0.006770501,0.0003833692,0.003008483],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1353401,"threshold_uncertainty_score":0.9854867,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009993076417919413,"score_gpt":0.2445374219458523,"score_spread":0.2345443455279329,"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."}}