{"id":"W4394293835","doi":"10.6084/m9.figshare.17020928","title":"Additional file 1 of Identification of candidate genes and enriched biological functions for feed efficiency traits by integrating plasma metabolites and imputed whole genome sequence variants in beef cattle","year":2021,"lang":"en","type":"dataset","venue":"Figshare","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada; University of Alberta","funders":"","keywords":"Biology; Identification (biology); Whole genome sequencing; Genetics; Gene; Computational biology; Genome; Biotechnology","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001273362,0.001429002,0.001544168,0.001406848,0.0009637616,0.001782047,0.002277252,0.001803483,0.4536733],"category_scores_gemma":[0.01114657,0.0006006265,0.001213241,0.002540805,0.0003159916,0.00100352,0.00106691,0.001081378,0.06986446],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008593283,"about_ca_system_score_gemma":0.001305296,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01104981,"about_ca_topic_score_gemma":0.02318819,"domain_scores_codex":[0.9994143,0.00009049677,0.0000779823,0.0002411704,0.00008118603,0.00009482208],"domain_scores_gemma":[0.9957485,0.002751419,0.0003600525,0.0004285269,0.0004969847,0.0002146014],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007367472,0.0001365658,0.01301776,0.004625029,0.0002608381,0.0001828172,0.00008978025,0.0008013588,0.0006632482,0.0006710517,0.9705376,0.008277189],"study_design_scores_gemma":[0.008757988,0.0004548255,0.1090977,0.003434549,0.000859232,0.001133503,0.0004432296,0.003519641,0.001830926,0.007157256,0.8630974,0.0002136423],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002274519,0.00002275262,0.00008988724,0.00002614309,0.000007453666,0.00001609551,0.9994091,0.00006662752,0.0001345962],"genre_scores_gemma":[0.002746628,0.00004977363,0.0009218328,0.0001341272,0.00001916448,0.0003542514,0.9945158,0.000115797,0.001142534],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4536733,"threshold_uncertainty_score":0.7792687,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02015592777587635,"score_gpt":0.2459157896467799,"score_spread":0.2257598618709036,"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."}}