{"id":"W4407007595","doi":"10.3390/microorganisms13020310","title":"Impact of Feed Composition on Rumen Microbial Dynamics and Phenotypic Traits in Beef Cattle","year":2025,"lang":"en","type":"article","venue":"Microorganisms","topic":"Ruminant Nutrition and Digestive Physiology","field":"Agricultural and Biological Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; University of British Columbia; Agriculture and Agri-Food Canada; University of Alberta","funders":"Alberta Livestock and Meat Agency; Alberta Innovates; Alberta Innovates - Technology Futures","keywords":"Rumen; Biology; Ruminant; Microbiome; Methanogen; Dry matter; Forage; Beef cattle; Animal science; Randomized block design; Food science; Animal feed; Agronomy; Fermentation; Bacteria; Pasture; Genetics","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":[],"consensus_categories":[],"category_scores_codex":[0.00004223104,0.0000899231,0.0001610419,0.00002722256,0.00005451392,0.00001318694,0.00007889322,0.00007171518,0.0000715072],"category_scores_gemma":[0.000006365371,0.00004063907,0.00004465145,0.0002095836,0.00006991815,0.0000307013,0.00002979325,0.00006681581,0.000007870805],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005960207,"about_ca_system_score_gemma":0.000008907104,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002588175,"about_ca_topic_score_gemma":0.0002638945,"domain_scores_codex":[0.9994863,0.00004352656,0.0001371823,0.000164733,0.00003112712,0.0001370934],"domain_scores_gemma":[0.9998178,0.00006652708,0.00004002645,0.00002269921,0.00002631189,0.00002661589],"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":[0.00009582401,0.000210772,0.007311324,0.000005753044,0.000006659055,5.683717e-7,0.00003449738,0.0000030288,0.9851012,0.001171745,0.0001880452,0.005870607],"study_design_scores_gemma":[0.0003381294,0.0003263821,0.8863302,0.00003480529,0.000004189819,0.000002259417,0.0000418508,0.0000143203,0.1118753,0.0009355767,0.00002642205,0.00007049309],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985096,0.00004079041,0.000005387018,0.0007072819,0.00003327614,0.000124238,0.0001252146,0.00001315119,0.0004410934],"genre_scores_gemma":[0.9995739,0.00001469547,0.00003843722,0.0001392837,0.00001728744,0.000002208124,0.000130965,6.295752e-7,0.00008256416],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8790189,"threshold_uncertainty_score":0.1657213,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008077240896684976,"score_gpt":0.2297076796612704,"score_spread":0.2216304387645854,"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."}}