{"id":"W3110250610","doi":"10.3389/fmicb.2020.595910","title":"A Comparative Evaluation of Tools to Predict Metabolite Profiles From Microbiome Sequencing Data","year":2020,"lang":"en","type":"article","venue":"Frontiers in Microbiology","topic":"Gut microbiota and health","field":"Biochemistry, Genetics and Molecular Biology","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Canadian Institutes of Health Research; Pacific Northwest National Laboratory; National Institutes of Health; National Institute on Drug Abuse; Small Business Innovation Research","keywords":"Metabolome; Metabolomics; Microbiome; Computational biology; Metagenomics; Metabolite; Amplicon sequencing; Biology; Human microbiome; Human Microbiome Project; Bioinformatics; Genetics; Gene; 16S ribosomal RNA; Biochemistry","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":[0.01477186,0.002419645,0.0009282849,0.003796062,0.000702626,0.00157542,0.001795012,0.001589827,0.001019236],"category_scores_gemma":[0.02413286,0.0005709673,0.00167346,0.002035064,0.0005539207,0.002855646,0.001616048,0.001381551,0.0008035846],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001041551,"about_ca_system_score_gemma":0.001883737,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008549944,"about_ca_topic_score_gemma":0.007435049,"domain_scores_codex":[0.994778,0.002214405,0.0004118696,0.001385157,0.0008897759,0.0003207653],"domain_scores_gemma":[0.9839512,0.01195423,0.0005851131,0.001067202,0.00204703,0.0003952639],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004673537,0.002168436,0.1076066,0.001196606,0.00255515,0.0004249746,0.0003108896,0.3524907,0.02068756,0.001746388,0.007641548,0.4984976],"study_design_scores_gemma":[0.0000919244,0.0007451483,0.01273103,0.00004146975,0.0001318508,0.0001015407,0.00007827914,0.9762189,0.007955529,0.0007955566,0.001064844,0.00004391878],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.6970078,0.003742249,0.2709256,0.00107305,0.0002840219,0.0005922107,0.005216619,0.01741613,0.003742277],"genre_scores_gemma":[0.7824147,0.0009444317,0.2024746,0.0002881021,0.00008346476,0.0003024735,0.01223572,0.0004473227,0.0008091399],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.01477186,"threshold_uncertainty_score":0.07812196,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1001329769880224,"score_gpt":0.331069409366413,"score_spread":0.2309364323783907,"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."}}