{"id":"W3033136034","doi":"10.3390/metabo10060233","title":"The Bovine Metabolome","year":2020,"lang":"en","type":"article","venue":"Metabolites","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":126,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada; University of Alberta","funders":"Alberta Innovates; Alberta Innovates - Technology Futures; Alberta Livestock and Meat Agency; Agriculture Funding Consortium; Genome Canada","keywords":"Metabolome; Computational biology; Biology; Metabolomics; Bioinformatics","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":[0.0002374701,0.000167958,0.0002165132,0.00001798791,0.0002438325,0.0000602738,0.0003249069,0.0000517048,0.00003967143],"category_scores_gemma":[0.0005496235,0.0001064483,0.0001406945,0.0002032191,0.0001104507,0.000003061411,0.0002218744,0.00008961991,0.00005844632],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000207626,"about_ca_system_score_gemma":0.00002679587,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004100947,"about_ca_topic_score_gemma":0.000005319756,"domain_scores_codex":[0.9989434,0.00006840729,0.0002106046,0.0003185463,0.000145143,0.0003139044],"domain_scores_gemma":[0.9993874,0.00002976109,0.00007156665,0.0003153431,0.00007542075,0.0001204387],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001248935,0.0000243365,0.002706376,0.00000849236,0.0002931826,0.000001593052,0.00005954324,0.000003594869,0.949471,0.02208878,0.01897356,0.006244644],"study_design_scores_gemma":[0.000222159,0.00009843889,0.003324036,4.419808e-7,0.00003985267,0.000001842143,0.00006642154,0.00001871753,0.1545498,0.0002792075,0.8412725,0.0001265337],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7823071,0.1852284,0.001967644,0.0163309,0.000726354,0.0004016979,0.0000705264,0.00007883619,0.01288849],"genre_scores_gemma":[0.9843904,0.00806596,0.001608783,0.002699008,0.001119935,0.00003778017,0.00003379771,0.00003005036,0.002014297],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.822299,"threshold_uncertainty_score":0.4340837,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01299639804873454,"score_gpt":0.2335748527713652,"score_spread":0.2205784547226307,"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."}}