{"id":"W3169142344","doi":"10.21203/rs.3.rs-104578/v1","title":"New mechanistic insight into the digestion of complex dietary fibre by rumen microbiota using combinatorial high-resolution glycomic and transcriptomic analyses","year":2020,"lang":"en","type":"preprint","venue":"Research Square","topic":"Ruminant Nutrition and Digestive Physiology","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"Biological and Environmental Research; Alberta Agriculture and Forestry; Center for Bioenergy Innovation; Oak Ridge National Laboratory; Agriculture and Agri-Food Canada; U.S. Department of Energy","keywords":"Rumen; Biology; Digestion (alchemy); Ruminococcus; Metagenomics; Glycome; Food science; Straw; Biochemistry; Xylanase; Glycan; Gut flora; Chemistry; Gene; Enzyme; Agronomy","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":[0.0003808964,0.0004156322,0.0003984392,0.0004238985,0.0002402362,0.0009599605,0.0001988027,0.0003566429,0.0008108141],"category_scores_gemma":[0.0002083468,0.00018368,0.0004449344,0.0005073855,0.0003180678,0.0005086031,0.0003506555,0.0006486498,0.0002093666],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003072737,"about_ca_system_score_gemma":0.000296006,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004671174,"about_ca_topic_score_gemma":0.0009216049,"domain_scores_codex":[0.9998515,0.00001888991,0.000007950975,0.00005455505,0.00003208711,0.00003503624],"domain_scores_gemma":[0.9998617,0.00003412196,0.00003783922,0.00001733178,0.00002648914,0.00002257164],"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":[0.0001651537,0.000030433,0.004361927,0.000120177,0.00003791727,0.00005907332,0.00004264771,0.000463542,0.9897451,0.0002905492,0.00006862447,0.004614934],"study_design_scores_gemma":[0.0000482991,0.0008566309,0.3502868,0.0001134178,0.0002904484,0.0006796935,0.001166074,0.04325435,0.5851884,0.005496478,0.01252906,0.00009044343],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9681682,0.001865766,0.02487511,0.0002202598,0.00003195454,0.00005509158,0.003504059,0.0001039069,0.001175622],"genre_scores_gemma":[0.9621845,0.001760956,0.02965361,0.0003078611,0.00004012282,0.0001020233,0.004299161,0.00004609246,0.001605699],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009599605,"threshold_uncertainty_score":0.002712429,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1449441187792579,"score_gpt":0.365028975865778,"score_spread":0.2200848570865201,"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."}}