{"id":"W3038111896","doi":"10.1074/mcp.r120.002051","title":"Proteomics and Metaproteomics Add Functional, Taxonomic and Biomass Dimensions to Modeling the Ecosystem at the Mucosal-luminal Interface","year":2020,"lang":"en","type":"review","venue":"Molecular & Cellular Proteomics","topic":"Gut microbiota and health","field":"Biochemistry, Genetics and Molecular Biology","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; Ministero dello Sviluppo Economico; Government of Canada; Genome Canada; Ontario Genomics; Ontario Ministry of Economic Development and Innovation; Ontario Genomics Institute","keywords":"Metaproteomics; Proteomics; Microbiome; Metagenomics; Computational biology; Computer science; Energy flow; Ecosystem; Ecology; Biology; Biochemical engineering; Bioinformatics; Energy (signal processing); 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001635237,0.001750788,0.00249327,0.003202517,0.0003051077,0.002059728,0.001205798,0.001963143,0.00236835],"category_scores_gemma":[0.001557077,0.00065301,0.001235115,0.00318766,0.0009905734,0.002826019,0.001325119,0.003790355,0.001905379],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009615903,"about_ca_system_score_gemma":0.001520813,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001083452,"about_ca_topic_score_gemma":0.0017368,"domain_scores_codex":[0.999544,0.0001108864,0.00004244096,0.00009569273,0.0001738517,0.00003317416],"domain_scores_gemma":[0.998613,0.0008625184,0.0001122274,0.00006129938,0.0002635726,0.00008737343],"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":[0.00005223221,0.00006093375,0.0005105584,0.0240048,0.0004120502,0.0002075577,0.00007385638,0.002334898,0.006166999,0.02567063,0.01597008,0.9245355],"study_design_scores_gemma":[0.0000124004,0.0001203896,0.001266906,0.003463105,0.0003603574,0.0008472741,0.0001064175,0.001057279,0.002400778,0.01945944,0.9708329,0.00007269037],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001953123,0.9943132,0.002812234,0.000613767,0.0004761401,0.000008199148,0.0000479022,0.00002676382,0.001506448],"genre_scores_gemma":[0.001153537,0.9947714,0.002815433,0.0003286493,0.0003498325,0.00001508172,0.00005678515,0.000008444651,0.0005007794],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.003202517,"threshold_uncertainty_score":0.008648098,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03187323177922467,"score_gpt":0.2689781381810543,"score_spread":0.2371049064018297,"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."}}