{"id":"W4285319089","doi":"10.21926/rpn.2202014","title":"The Potential Role of Commensal Microbes in Optimizing Nutrition Care Delivery and Nutrient Metabolism","year":2022,"lang":"en","type":"article","venue":"Recent Progress in Nutrition","topic":"Gut microbiota and health","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Metagenomics; Biology; Gut flora; Microbiome; Biotechnology; Microbial metabolism; Host (biology); Commensalism; Human health; Computational biology; Bacteria; Bioinformatics; Ecology; Medicine; Environmental health; Immunology; Genetics","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":[0.0002005905,0.00009612172,0.0001338198,0.00008716801,0.0001745619,0.00002011144,0.000111979,0.00007119099,0.000004327904],"category_scores_gemma":[0.000005017359,0.00009395954,0.0000391638,0.0001406982,0.0000778067,0.000006134018,0.0001595134,0.0001555748,1.795141e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006211238,"about_ca_system_score_gemma":0.00003853928,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002093622,"about_ca_topic_score_gemma":0.00003997352,"domain_scores_codex":[0.9990091,0.0001900756,0.000259309,0.000221102,0.0001025116,0.0002179103],"domain_scores_gemma":[0.9996637,0.000008983308,0.00009342777,0.0001314854,0.00007278586,0.00002958278],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001440589,0.002084792,0.008149911,0.00069822,0.00003093899,0.0000104179,0.0007669991,0.00006085412,0.9373814,0.0005267367,0.0007522668,0.04809682],"study_design_scores_gemma":[0.012931,0.001168748,0.01466627,0.0005453522,0.00005510635,0.0001179149,0.01963594,0.0003649408,0.5432904,0.0009178803,0.4056978,0.0006086559],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8316762,0.1671564,0.000008343376,0.0004180959,0.0001131951,0.0005527461,0.00005657767,0.000004318813,0.00001413964],"genre_scores_gemma":[0.944485,0.05400816,0.0007737907,0.00004845948,0.00006455585,0.0002395627,0.0003668427,0.00001102831,0.000002604033],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4049455,"threshold_uncertainty_score":0.3831559,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004822381121228376,"score_gpt":0.2392483980849426,"score_spread":0.2344260169637142,"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."}}