{"id":"W2413753500","doi":"10.1021/acs.analchem.6b01412","title":"<i>In Vitro</i> Metabolic Labeling of Intestinal Microbiota for Quantitative Metaproteomics","year":2016,"lang":"en","type":"letter","venue":"Analytical Chemistry","topic":"Gut microbiota and health","field":"Biochemistry, Genetics and Molecular Biology","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; Crohn's and Colitis Canada; Canada Research Chairs; Faculty of Medicine, University of Ottawa; Ontario Genomics Institute; CHEO Research Institute; Ontario Ministry of Economic Development and Innovation; Institute of Infection and Immunity; Canadian Institutes of Health Research; Genome Canada","keywords":"Chemistry; Metaproteomics; In vitro; Chromatography; Biochemistry; Food science; Computational biology; Metagenomics","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":[0.002631027,0.00095219,0.0006535013,0.0004776246,0.0008174408,0.001722986,0.001044352,0.006094228,0.00454042],"category_scores_gemma":[0.004940791,0.0003648197,0.0004625236,0.0005438915,0.002207653,0.0009965118,0.0006177739,0.006756776,0.006828112],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001716694,"about_ca_system_score_gemma":0.0004319694,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002494251,"about_ca_topic_score_gemma":0.0005364333,"domain_scores_codex":[0.9966576,0.001704201,0.0002312697,0.0003559626,0.0008731598,0.0001777293],"domain_scores_gemma":[0.9968906,0.001639598,0.0003800488,0.000441631,0.0004578988,0.0001903066],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0006729985,0.0002362029,0.00233503,0.001266553,0.00009940346,0.006241763,0.0002295892,0.0007102287,0.207293,0.02136314,0.6662887,0.09326326],"study_design_scores_gemma":[0.0001324843,0.0005627509,0.002286792,0.0001809763,0.00006560755,0.01475411,0.0001965247,0.006113725,0.1593201,0.01261728,0.8036889,0.0000806442],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"methods","genre_scores_codex":[0.02412808,0.05179597,0.06080066,0.7004062,0.09716227,0.0005057787,0.001086966,0.002206518,0.06190758],"genre_scores_gemma":[0.2633513,0.05640309,0.07375361,0.452387,0.1013221,0.0018456,0.001391304,0.0006556485,0.04889028],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.006094228,"threshold_uncertainty_score":0.01518917,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02026251345219479,"score_gpt":0.2984569909798928,"score_spread":0.278194477527698,"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."}}