{"id":"W4394414890","doi":"10.6084/m9.figshare.17020934","title":"Additional file 3 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":"Identification (biology); Biology; Gene; Genetics; Computational biology; Whole genome sequencing; Genome; Beef cattle; Candidate gene; 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":[0.001060612,0.001309811,0.001560197,0.001696688,0.0008117615,0.001677996,0.002014677,0.001538357,0.5117487],"category_scores_gemma":[0.008806154,0.000543607,0.001172962,0.002789251,0.0003070813,0.0008577777,0.001069427,0.0009994222,0.0800345],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008369939,"about_ca_system_score_gemma":0.001265782,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01059931,"about_ca_topic_score_gemma":0.02054144,"domain_scores_codex":[0.9995199,0.00007887361,0.00006366525,0.0001850172,0.00007726733,0.00007528556],"domain_scores_gemma":[0.9952165,0.003406799,0.0003288471,0.0003238084,0.0005011327,0.000222918],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0005110661,0.00009579796,0.005929072,0.003652457,0.0001901932,0.0001217081,0.00006942749,0.0007141599,0.000470339,0.0007085526,0.9819874,0.005549898],"study_design_scores_gemma":[0.006408954,0.000267345,0.05699067,0.002308216,0.0006151477,0.0006950338,0.0002800128,0.002144512,0.001544,0.007424724,0.9211783,0.0001431439],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001221247,0.00001704352,0.00005679119,0.00002084304,0.000004833359,0.000009227052,0.99954,0.00006896025,0.0001602336],"genre_scores_gemma":[0.001756292,0.0000423258,0.0005598369,0.0001024413,0.00001167259,0.0002132589,0.9961579,0.0001105587,0.001045724],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.5117487,"threshold_uncertainty_score":0.6964313,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01986921484229453,"score_gpt":0.2456214339026542,"score_spread":0.2257522190603596,"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."}}