{"id":"W2993673687","doi":"10.1093/jas/skz258.170","title":"98 Effect of engineered biocarbon on rumen fermentation, nutrient digestibility, methane emissions, and rumen microbiota in beef heifers","year":2019,"lang":"en","type":"article","venue":"Journal of Animal Science","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; University of Lethbridge; University of Calgary","funders":"","keywords":"Rumen; Latin square; Animal science; Dry matter; Fermentation; Silage; Feces; Beef cattle; Digestion (alchemy); Biology; Chemistry; Agronomy; Food science; Microbiology; Chromatography","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0002412613,0.000234553,0.0003199528,0.0001440068,0.00021396,0.0004431587,0.0001458081,0.0001771945,0.0005711676],"category_scores_gemma":[0.0002158823,0.0001599841,0.0001661536,0.0001441457,0.0002579936,0.0002212665,0.0002594747,0.0003489474,0.00007503016],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000602124,"about_ca_system_score_gemma":0.0002630391,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004351884,"about_ca_topic_score_gemma":0.00913609,"domain_scores_codex":[0.9997647,0.00004741878,0.0000192291,0.00006032063,0.00005790538,0.00005046105],"domain_scores_gemma":[0.9997926,0.00003455318,0.00006704215,0.00001786713,0.00003230878,0.00005553348],"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":[0.002620617,0.0003276484,0.005203923,0.00004740103,0.00003821966,0.00004341226,0.00004868378,0.0002335355,0.9877379,0.00002220328,0.00001766244,0.003658734],"study_design_scores_gemma":[0.00007869759,0.01054383,0.1575114,0.00002056861,0.0001032106,0.0001434426,0.0004111841,0.001896831,0.8274729,0.00005307418,0.001737663,0.00002715025],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9997655,0.00004968662,0.00009031403,0.000004847667,0.000001456764,0.000002807456,0.00003485633,0.000002019265,0.00004863261],"genre_scores_gemma":[0.9984857,0.000089573,0.000612809,0.00002547392,0.000001533862,0.000009472617,0.0001266138,0.000005051484,0.0006436586],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004351884,"threshold_uncertainty_score":0.008653104,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009860438264656808,"score_gpt":0.2508193539334163,"score_spread":0.2409589156687595,"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."}}