{"id":"W4214825972","doi":"10.2337/db21-1046","title":"Connecting Genomics and Proteomics to Identify Protein Biomarkers for Adult and Youth-Onset Type 2 Diabetes: A Two-Sample Mendelian Randomization Study","year":2022,"lang":"en","type":"article","venue":"Diabetes","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Jewish General Hospital; Université de Montréal","funders":"","keywords":"Mendelian randomization; Genomics; Proteomics; Computational biology; Genetics; Mendelian inheritance; Biology; Type 2 diabetes; Bioinformatics; Medicine; Diabetes mellitus; Gene; Endocrinology; Genome; Genetic variants; Genotype","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":[],"consensus_categories":[],"category_scores_codex":[0.01605348,0.001257268,0.001107497,0.001106166,0.0004783396,0.0007109491,0.0006709622,0.001389846,0.001631165],"category_scores_gemma":[0.02157123,0.0004880346,0.001612721,0.0008644719,0.0007533464,0.0004818299,0.0007049778,0.0006916447,0.0001602788],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000305332,"about_ca_system_score_gemma":0.0004614402,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001133504,"about_ca_topic_score_gemma":0.0005600605,"domain_scores_codex":[0.9813793,0.01477651,0.0005258879,0.002028382,0.0009799468,0.0003100616],"domain_scores_gemma":[0.989939,0.005705978,0.001514836,0.002100402,0.0003926798,0.0003469514],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.03643105,0.001625203,0.8013632,0.0004569032,0.01336147,0.005573693,0.001134046,0.002589118,0.05343689,0.008094317,0.002464323,0.07346983],"study_design_scores_gemma":[0.008060508,0.01789282,0.8587682,0.0001243559,0.01428065,0.0143536,0.0005094021,0.05275728,0.01202971,0.0106641,0.01028724,0.0002720041],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9483028,0.00131618,0.04839002,0.0004874305,0.0001195055,0.0002607125,0.0003002474,0.0001619247,0.0006611894],"genre_scores_gemma":[0.9769133,0.0002265464,0.02168967,0.0003462282,0.00004892768,0.000220156,0.0001545994,0.00003713854,0.000363499],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01605348,"threshold_uncertainty_score":0.08489996,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01493383815248428,"score_gpt":0.2781755800944681,"score_spread":0.2632417419419838,"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."}}