{"id":"W7161943675","doi":"10.82308/17138","title":"Integrating metabolomics and genomics to identify biomarkers and drug targets for diseases","year":2024,"lang":"en","type":"dissertation","venue":"","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mendelian randomization; Metabolomics; Genome-wide association study; Disease; Metabolite; Genetic association; Genomics; Metabolome; Mendelian inheritance; Genetic architecture","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003457709,0.0008418265,0.00175384,0.002815048,0.0003650815,0.003047232,0.0006510855,0.001051702,0.00364646],"category_scores_gemma":[0.00323327,0.0003888371,0.001605514,0.001629871,0.0009522044,0.001754097,0.001691997,0.002093902,0.0009038777],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00115373,"about_ca_system_score_gemma":0.002364091,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002502319,"about_ca_topic_score_gemma":0.004068248,"domain_scores_codex":[0.9989564,0.0004416909,0.00005049281,0.0002072702,0.0002442871,0.0000998122],"domain_scores_gemma":[0.9985183,0.0007017454,0.0002382717,0.0001621664,0.0002567496,0.000122757],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0009169439,0.0005904236,0.0568506,0.005392903,0.003885076,0.000693139,0.0007040685,0.009277415,0.04538178,0.05542168,0.01920143,0.8016846],"study_design_scores_gemma":[0.0004292262,0.003190885,0.1239685,0.003828304,0.004070785,0.002497927,0.001506534,0.02735644,0.04128873,0.3095469,0.4818509,0.0004648758],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.1213708,0.557431,0.1859122,0.0833517,0.002684542,0.0007303574,0.004669233,0.001396284,0.04245392],"genre_scores_gemma":[0.3818066,0.4212124,0.164541,0.0181521,0.002616854,0.000434418,0.001708249,0.0002114085,0.009317047],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00364646,"threshold_uncertainty_score":0.01828635,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007235072327236662,"score_gpt":0.2916477325735243,"score_spread":0.2844126602462877,"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."}}