{"id":"W4200570320","doi":"10.1016/j.csbj.2021.12.012","title":"Inferring early-life host and microbiome functions by mass spectrometry-based metaproteomics and metabolomics","year":2021,"lang":"en","type":"review","venue":"Computational and Structural Biotechnology Journal","topic":"Gut microbiota and health","field":"Biochemistry, Genetics and Molecular Biology","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Cumming School of Medicine, University of Calgary; Alberta Children's Hospital Research Institute; Fundação Oswaldo Cruz; Norges Forskningsråd; Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro; W. Garfield Weston Foundation; Canadian Institutes of Health Research; Sick Kids Foundation","keywords":"Metaproteomics; Microbiome; Computational biology; Metabolomics; Biology; Gut microbiome; Metagenomics; Human microbiome; Identification (biology); Omics; Bioinformatics; Ecology; Gene; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001661199,0.0004142085,0.0009087314,0.0003209053,0.0004401157,0.0001651204,0.0001615601,0.0008446588,0.00001322246],"category_scores_gemma":[0.00006464725,0.0003468605,0.0001685603,0.0002168475,0.0003887849,0.00001032581,0.0001857095,0.0008333555,0.000001324163],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003748568,"about_ca_system_score_gemma":0.0003876941,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005237343,"about_ca_topic_score_gemma":0.000001979079,"domain_scores_codex":[0.9983912,0.0001150001,0.0005276974,0.0005451582,0.00008708927,0.0003338472],"domain_scores_gemma":[0.9991303,0.0000419287,0.0003685939,0.0001542315,0.000101915,0.0002030348],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001376748,0.00009780514,0.0009896905,0.006419667,0.004683153,0.0001059602,0.00006559133,0.0001148113,0.4863188,0.002811967,0.00420516,0.4940498],"study_design_scores_gemma":[0.002879944,0.0009758656,0.002119774,0.00154995,0.001811286,0.01380015,0.0001009701,0.0003763339,0.002424073,0.001331236,0.9705099,0.002120456],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.05740009,0.9317351,0.009505334,0.000571313,0.000189076,0.0002235976,0.0003562071,0.00001646963,0.000002806866],"genre_scores_gemma":[0.004799529,0.9721816,0.02189706,0.0002092216,0.0001609056,0.000006448389,0.0006633634,0.00003612093,0.00004580416],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9663048,"threshold_uncertainty_score":0.9998983,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0135740744053331,"score_gpt":0.2740460071332131,"score_spread":0.2604719327278801,"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."}}