{"id":"W2010677870","doi":"10.4141/a05-003","title":"Modeling nutrient supply to dairy cattle from a feedstuff using NRC-2001 (a TDN-based model) with inputs based on in situ and mobile bag technique measurements","year":2005,"lang":"en","type":"article","venue":"Canadian Journal of Animal Science","topic":"Ruminant Nutrition and Digestive Physiology","field":"Agricultural and Biological Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Wageningen University and Research","keywords":"Rumen; Digestion (alchemy); Nutrient; Dairy cattle; Protein degradation; Animal science; Abomasum; In situ; Chemistry; Food science; Biology; Agronomy; Biotechnology; Biochemistry; Chromatography; Fermentation","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0004941594,0.0007683221,0.0006688709,0.0002723548,0.0004068916,0.0007722405,0.001129049,0.001263899,0.001293191],"category_scores_gemma":[0.0009246939,0.0004752156,0.0007683281,0.0003913747,0.0003791007,0.0005045225,0.0003151027,0.0006557007,0.0002481021],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002534821,"about_ca_system_score_gemma":0.001695325,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1010841,"about_ca_topic_score_gemma":0.05348463,"domain_scores_codex":[0.9998146,0.00005678166,0.000009766634,0.00005466511,0.00003625784,0.00002796364],"domain_scores_gemma":[0.9995491,0.0002260666,0.00005771279,0.00002085468,0.0001174396,0.00002879563],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006225907,0.00002644111,0.002199884,0.00001884708,0.00001688858,0.00002025582,0.000008350803,0.9960185,0.0008323715,0.0001206043,0.0000412571,0.0006344867],"study_design_scores_gemma":[0.00001816718,0.00003312093,0.0007209551,0.000002450393,0.00001139614,0.00000469268,0.000007534005,0.9986445,0.0003865178,0.00005844221,0.0001078166,0.000004373274],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9789723,0.0001274302,0.01474602,0.0001331195,0.00002465556,0.0000505389,0.0008571949,0.0001463917,0.004942361],"genre_scores_gemma":[0.9910911,0.00008907182,0.006357653,0.00004236032,0.00000656061,0.0000960274,0.0006236385,0.00002606205,0.001667415],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1010841,"threshold_uncertainty_score":0.2009913,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04668667750328814,"score_gpt":0.2519700307235838,"score_spread":0.2052833532202956,"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."}}