{"id":"W4394295339","doi":"10.6084/m9.figshare.22601141","title":"Additional file 17 of Implicating genes, pleiotropy, and sexual dimorphism at blood lipid loci through multi-ancestry meta-analysis","year":2023,"lang":"en","type":"dataset","venue":"UWA Profiles and Research Repository (UWA)","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Clinical Evaluative Sciences; Children's Hospital of Eastern Ontario; University of Toronto; University of Ottawa; Université de Montréal; Université Laval; Ottawa Hospital; Montreal Heart Institute","funders":"","keywords":"Sexual dimorphism; Pleiotropy; Biology; Meta-analysis; Genetics; Gene; Evolutionary biology; Computational biology; Bioinformatics; Phenotype; Medicine; Zoology; Internal medicine","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005042324,0.0004550977,0.001212561,0.0002839568,0.0007679863,0.00009753788,0.0004573012,0.0005232376,0.003904701],"category_scores_gemma":[0.0004366554,0.0003612729,0.0005058142,0.0004930627,0.0007414658,0.00001069294,0.001635061,0.0005395439,0.0000175539],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002645179,"about_ca_system_score_gemma":0.0001794082,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007171555,"about_ca_topic_score_gemma":0.00004484232,"domain_scores_codex":[0.9963939,0.0003494188,0.000640926,0.001279845,0.0007073982,0.0006284876],"domain_scores_gemma":[0.9975102,0.0004669742,0.0004759103,0.0009597595,0.0003984914,0.0001886766],"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":[0.00003307787,0.0001248338,0.00002860166,0.000308426,0.02828202,0.00002948455,0.00001125501,0.000002929025,0.04986615,0.000008494217,0.9212669,0.00003779081],"study_design_scores_gemma":[0.0002858297,0.0003561012,0.0005737825,0.00001727401,0.01030087,0.00005404788,0.0001487806,0.0000197281,0.05131684,0.0000138981,0.9365146,0.0003983098],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.004221143,0.01974892,0.000005526179,0.00008718402,0.00007059547,0.0004317965,0.9753273,0.00001295222,0.00009463394],"genre_scores_gemma":[0.0001794313,0.00814264,0.001928529,0.00003013298,0.0007575969,0.0009195838,0.9760172,0.0000444489,0.01198041],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01798116,"threshold_uncertainty_score":0.9998839,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.102366447270653,"score_gpt":0.3570154521151713,"score_spread":0.2546490048445183,"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."}}