{"id":"W2789874562","doi":"10.1503/cmaj.170846","title":"The genome, microbiome and evolutionary medicine","year":2018,"lang":"en","type":"article","venue":"Canadian Medical Association Journal","topic":"Digestive system and related health","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Centre for Disease Control; University of British Columbia","funders":"","keywords":"Evolutionary medicine; Microbiome; Genomics; Genomic medicine; Genome; Data science; Human microbiome; Computational biology; Biology; Bioinformatics; Computer science; Evolutionary biology; Genetics; Gene","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.001183054,0.00005984858,0.00007208101,0.00004182282,0.0006335258,0.00002208823,0.0001190194,0.0002527675,0.0002292613],"category_scores_gemma":[0.0006402709,0.00003793119,0.00002247835,0.00007594507,0.0001946337,0.000002406902,0.00001555876,0.0002167696,0.00004829262],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001423862,"about_ca_system_score_gemma":0.001134832,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004853708,"about_ca_topic_score_gemma":0.006666646,"domain_scores_codex":[0.9990304,0.0001171832,0.0002052764,0.00009776405,0.0002740914,0.0002753605],"domain_scores_gemma":[0.9988158,0.00003019505,0.0001009355,0.00006451062,0.000300175,0.0006883728],"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":[0.00002481594,0.00001352115,0.03368442,0.000009369235,0.0002612325,0.00005462605,0.0002962984,5.165878e-7,0.006092214,0.0006431136,0.937735,0.02118489],"study_design_scores_gemma":[0.0003048264,0.000136216,0.04413529,0.00002011511,0.000005857899,0.0004154275,0.0001482578,0.000004763875,0.00002708614,0.00009111535,0.9546601,0.00005090355],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7017999,0.02350834,0.0003462672,0.2168342,0.005097704,0.0003474398,0.00005057372,0.00001631379,0.05199924],"genre_scores_gemma":[0.9797755,0.002301177,0.00003344314,0.007446907,0.005970446,0.000002356459,0.00002028917,0.00001121656,0.004438682],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2779755,"threshold_uncertainty_score":0.4872632,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003810705617269303,"score_gpt":0.2284824985294508,"score_spread":0.2246717929121815,"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."}}