{"id":"W3148165551","doi":"10.1101/2021.03.29.437612","title":"Ultra-sensitive isotope probing to quantify activity and substrate assimilation in microbiomes","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"National Institutes of Health; Canada First Research Excellence Fund; National Institute of Food and Agriculture; Novo Nordisk Fonden; National Institute of General Medical Sciences; Novo Nordisk; U.S. Department of Agriculture; Natural Sciences and Engineering Research Council of Canada; Government of Alberta; Foundation for Food and Agriculture Research; University of Calgary; National Science Foundation","keywords":"Stable-isotope probing; Metaproteomics; Microbiome; Isotope; Isotopic labeling; Biology; Biogeochemical cycle; Stable isotope ratio; Metagenomics; Computational biology; Chemistry; Bioinformatics; Bacteria; Biochemistry; Genetics; Ecology; Gene","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":[0.0002533871,0.0004446119,0.0004835239,0.0001784755,0.0001285271,0.00024257,0.0002353449,0.0005316638,0.00001905956],"category_scores_gemma":[0.00008270229,0.0005435679,0.00008006147,0.0004189598,0.00007188973,0.0001695265,0.0002861052,0.0008488264,0.000005191757],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003151358,"about_ca_system_score_gemma":0.0002618531,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001051572,"about_ca_topic_score_gemma":0.00002269769,"domain_scores_codex":[0.9979082,0.00004380887,0.0003979178,0.001098083,0.0001458867,0.0004061108],"domain_scores_gemma":[0.9983815,0.00006258024,0.0003110254,0.0008158294,0.0002620821,0.0001669886],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002229073,0.00008647525,0.002783222,0.0003168876,0.0000311652,0.00002376521,0.0000354858,0.0001236748,0.9964119,0.0001507079,0.000007841142,0.000006649004],"study_design_scores_gemma":[0.0001859752,0.000007706067,0.02610342,0.0006461699,0.00002607941,3.914811e-8,0.00001218152,0.0002497015,0.971984,0.000004452912,0.0002065424,0.0005736792],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9842761,0.0001362296,0.01394342,0.0002848875,0.00006906213,0.0007408435,0.0002350356,0.0002871844,0.00002719979],"genre_scores_gemma":[0.9663079,0.0002131123,0.03269506,0.00006926414,0.0000901373,0.0005283376,0.000001673686,0.0000893445,0.000005204979],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02442778,"threshold_uncertainty_score":0.9997016,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01632804917841102,"score_gpt":0.2508357661040027,"score_spread":0.2345077169255917,"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."}}