{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004626702,0.0002951375,0.0005844416,0.0001000455,0.0001191384,0.00003436118,0.0003115101,0.0001386675,0.00002948115],"category_scores_gemma":[0.001016403,0.0002672432,0.0002784471,0.0003307599,0.0001255934,0.000009523233,0.0002289223,0.00009333601,0.000002533211],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005793309,"about_ca_system_score_gemma":0.00005557138,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000300411,"about_ca_topic_score_gemma":0.00001233923,"domain_scores_codex":[0.9981544,0.00008795227,0.0005307849,0.0005667452,0.0002012476,0.0004588407],"domain_scores_gemma":[0.9989371,0.00005305584,0.0002688396,0.000344857,0.0002366373,0.0001594593],"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":[0.0002825739,0.0000609004,0.02795881,0.00009381215,0.000912117,0.000001093521,0.0001868427,0.0000205994,0.965807,0.0017239,0.001430035,0.001522352],"study_design_scores_gemma":[0.001435086,0.0003282021,0.04818565,0.000007914341,0.0003565626,0.000004674626,0.0004992834,0.0002507564,0.8667221,0.0001472989,0.08171028,0.0003522028],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.959824,0.03330038,0.003135474,0.0008405967,0.0004385807,0.0005974599,0.0008358853,0.00004339891,0.0009842772],"genre_scores_gemma":[0.9880179,0.001404193,0.008764924,0.0004266251,0.0007922152,0.00006542267,0.0002066421,0.00005137506,0.0002707164],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09908488,"threshold_uncertainty_score":0.999978,"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."}}