{"id":"W2923081087","doi":"10.1101/585893","title":"A multi-omic cohort as a reference point for promoting a healthy human 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":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Toronto","keywords":"Microbiome; Gut microbiome; Metagenomics; Cohort; Human Microbiome Project; Omics; Biobank; Biology; Cohort study; Computational biology; Gut flora; Bioinformatics; Medicine; Human microbiome; Immunology; Genetics; Internal medicine","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006688294,0.0007479535,0.0008670076,0.001400861,0.001412818,0.002632206,0.0007737339,0.001089538,0.00516404],"category_scores_gemma":[0.009076837,0.0002976391,0.0009404804,0.001864781,0.0003268927,0.0008227991,0.002225964,0.001386717,0.001289627],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004446467,"about_ca_system_score_gemma":0.0009273262,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004050551,"about_ca_topic_score_gemma":0.00455638,"domain_scores_codex":[0.9976936,0.0008374747,0.0002149888,0.0006960577,0.0004090043,0.0001488349],"domain_scores_gemma":[0.9954644,0.0006539543,0.0007226857,0.001794006,0.0009424295,0.0004225237],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003107549,0.0004786143,0.8237222,0.0008762461,0.003693887,0.0006090181,0.001018812,0.001577812,0.05843899,0.005149285,0.03262768,0.06869988],"study_design_scores_gemma":[0.0002670005,0.000897381,0.9068689,0.0005021304,0.001790067,0.00110308,0.0007257856,0.002298331,0.01222202,0.005773626,0.067447,0.0001045513],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8060061,0.008590033,0.1007045,0.006122135,0.001672861,0.0008144589,0.06693014,0.00103057,0.008129205],"genre_scores_gemma":[0.8626497,0.001935239,0.09040598,0.003295416,0.0004861795,0.001244649,0.03491449,0.0005823803,0.004485994],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006688294,"threshold_uncertainty_score":0.03537154,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01994763468336104,"score_gpt":0.2779183583329496,"score_spread":0.2579707236495886,"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."}}