{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007958793,0.0007602681,0.0005720243,0.001333332,0.000358681,0.0008334844,0.0004712054,0.0008796226,0.001424959],"category_scores_gemma":[0.00126367,0.0004003135,0.0005010248,0.001037866,0.0004778047,0.000588489,0.001059639,0.0009870181,0.0009425738],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003066138,"about_ca_system_score_gemma":0.0003134583,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006259113,"about_ca_topic_score_gemma":0.0009055388,"domain_scores_codex":[0.9992588,0.0001312095,0.00003349913,0.0002282194,0.0002791096,0.00006914457],"domain_scores_gemma":[0.9994556,0.0002170618,0.0001110316,0.00006114718,0.0001140255,0.00004110434],"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":[0.00008094542,0.00002844884,0.002871236,0.0001914313,0.00003887143,0.00003348099,0.00006880575,0.0006087471,0.9851149,0.0002492458,0.0002830367,0.0104309],"study_design_scores_gemma":[0.00001433708,0.0002664271,0.01793534,0.00006670721,0.00007701523,0.0002892105,0.0001701023,0.02691832,0.9419309,0.001594707,0.01066977,0.00006707145],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5614091,0.005089089,0.4167231,0.0004550338,0.0002417379,0.0002282521,0.006850423,0.003168451,0.005834777],"genre_scores_gemma":[0.699839,0.002916066,0.2884384,0.0005188492,0.00009083714,0.000500911,0.003955697,0.0004188175,0.003321395],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001424959,"threshold_uncertainty_score":0.004767001,"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."}}