{"id":"W3108538230","doi":"10.3390/metabo10120491","title":"Serum Metabolite Biomarkers for Predicting Residual Feed Intake (RFI) of Young Angus Bulls","year":2020,"lang":"en","type":"article","venue":"Metabolites","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada; University of Alberta","funders":"Alberta Livestock and Meat Agency; Alberta Innovates; Alberta Innovates - Technology Futures; Genome Canada","keywords":"Residual feed intake; Feed conversion ratio; Metabolite; Metabolomics; Beef cattle; Chemistry; Chromatography; Livestock; Breed; Animal science; Mass spectrometry; Biotechnology; Food science; Biology; Body weight; Biochemistry; Endocrinology","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":[0.001225757,0.0006698716,0.0005230178,0.0008831721,0.0001851572,0.0008048594,0.0002052117,0.0006295008,0.0004965544],"category_scores_gemma":[0.0007967189,0.0001986331,0.0003010084,0.0004849946,0.0002072352,0.0002628569,0.0002285056,0.0005505264,0.0002492088],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002346241,"about_ca_system_score_gemma":0.0001671721,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002497036,"about_ca_topic_score_gemma":0.00456865,"domain_scores_codex":[0.9996202,0.00009256478,0.00002986753,0.0001203724,0.00009628345,0.00004061247],"domain_scores_gemma":[0.999411,0.0001257409,0.0001961669,0.00002984741,0.0001610584,0.0000761371],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001057726,0.0002134915,0.9114594,0.0001431333,0.0003484703,0.0001542305,0.0001144476,0.000562118,0.05951434,0.00005849349,0.0004207776,0.0259533],"study_design_scores_gemma":[0.00003315874,0.001485452,0.9718426,0.00007901083,0.0004389735,0.0005922807,0.0002335361,0.008395553,0.01529789,0.0001082252,0.001464546,0.00002891123],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9894713,0.005077105,0.003449464,0.00008938667,0.00003522245,0.0000443102,0.00094516,0.00009595461,0.000792098],"genre_scores_gemma":[0.9924447,0.001013321,0.004783867,0.0001532101,0.00003763512,0.00002830647,0.001011971,0.000008062681,0.0005189707],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002497036,"threshold_uncertainty_score":0.006482482,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01603541450105019,"score_gpt":0.2486366839519005,"score_spread":0.2326012694508504,"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."}}