{"id":"W2175093233","doi":"10.1038/ismej.2008.108","title":"Shotgun metaproteomics of the human distal gut microbiota","year":2008,"lang":"en","type":"article","venue":"The ISME Journal","topic":"Gut microbiota and health","field":"Biochemistry, Genetics and Molecular Biology","cited_by":542,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Ste. Anne's Hospital","funders":"Oak Ridge National Laboratory; National Institutes of Health; Universitetssjukhuset Örebro; U.S. Department of Energy; Örebro Universitet; Arnold and Mabel Beckman Initiative for Macular Research; UT-Battelle; Lawrence Berkeley National Laboratory; National Institute of General Medical Sciences; Battelle","keywords":"Metaproteomics; Metagenomics; Biology; Proteome; Computational biology; Shotgun proteomics; Microbiome; Human microbiome; Proteomics; Gut flora; Shotgun; Shotgun sequencing; Gene; Microbiology; Genetics; DNA sequencing; Biochemistry","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0003280597,0.0004206404,0.0004997613,0.001009999,0.0003124516,0.0004376524,0.0001912879,0.0003717801,0.000478858],"category_scores_gemma":[0.0003771558,0.000185782,0.0005024571,0.0007867691,0.000133315,0.0001415569,0.0004611909,0.0003336065,0.0002546874],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001499785,"about_ca_system_score_gemma":0.000208414,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008586699,"about_ca_topic_score_gemma":0.0009686433,"domain_scores_codex":[0.9997894,0.0000420269,0.00001103468,0.00006298758,0.00006461142,0.00002990536],"domain_scores_gemma":[0.9999204,0.00001513993,0.00001060615,0.00001286165,0.00002470771,0.00001637373],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0005700474,0.00004078763,0.01137954,0.0001459439,0.0001461003,0.0002186527,0.00009043239,0.0003564743,0.9749767,0.0001538732,0.0001877896,0.01173358],"study_design_scores_gemma":[0.00006764144,0.0009038578,0.4207697,0.00009506308,0.0007113875,0.004430218,0.000576278,0.01389721,0.5450774,0.002043385,0.01136426,0.0000635229],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.975441,0.006546624,0.01341186,0.0001743481,0.00003290563,0.00005287239,0.003124806,0.00009577534,0.001119958],"genre_scores_gemma":[0.9752454,0.003060775,0.01557003,0.0002549754,0.00002811193,0.00005523957,0.004767383,0.00003932096,0.0009787396],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001009999,"threshold_uncertainty_score":0.001734972,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01642312010991245,"score_gpt":0.2488616806131845,"score_spread":0.232438560503272,"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."}}