{"id":"W4394181012","doi":"10.6084/m9.figshare.22601162","title":"Additional file 18 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; Gene; Evolutionary biology; Genetics; Computational biology; Bioinformatics; Phenotype; Zoology; Medicine; 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":[0.0005019323,0.0004536826,0.001225561,0.0002879218,0.0007560488,0.00009764466,0.0004529425,0.0005182758,0.004946671],"category_scores_gemma":[0.00046716,0.0003612408,0.0005032037,0.0005091679,0.0007529074,0.00001062787,0.001646949,0.0005350549,0.00002029814],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002682341,"about_ca_system_score_gemma":0.0001831722,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008598069,"about_ca_topic_score_gemma":0.00004194904,"domain_scores_codex":[0.9963647,0.0003683489,0.0006430864,0.001289282,0.000707474,0.0006271151],"domain_scores_gemma":[0.9975146,0.0004694547,0.000470532,0.0009531569,0.0004037401,0.0001885251],"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":[0.0000347827,0.0001260047,0.00002772543,0.0003368989,0.02850499,0.00002931337,0.00001031446,0.00000241931,0.04523225,0.000009448761,0.9256368,0.00004904003],"study_design_scores_gemma":[0.0003030146,0.0003670368,0.0005802666,0.00001770941,0.01057789,0.00006040461,0.0001519293,0.00001960338,0.05803492,0.00001793986,0.9294593,0.0004099554],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.004233005,0.01955328,0.000006697661,0.00007403873,0.00007715279,0.0004317208,0.9755155,0.00001305482,0.00009556925],"genre_scores_gemma":[0.0002716438,0.00848063,0.002000239,0.00002798104,0.0007598042,0.000924568,0.9782881,0.00004601172,0.009200991],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0179271,"threshold_uncertainty_score":0.9998839,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.12141771907243,"score_gpt":0.3654832246876738,"score_spread":0.2440655056152438,"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."}}