{"id":"W4360797450","doi":"10.1101/2023.03.22.533869","title":"Gene-metabolite annotation with shortest reactional distance enhances metabolite genome-wide association studies results","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Montreal Heart Institute","funders":"Institute of Nutrition, Metabolism and Diabetes; National Institute of Diabetes and Digestive and Kidney Diseases; Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; Fondation Institut de Cardiologie de Montréal; Institut de Valorisation des Données; Institut de Cardiologie de Montréal; Génome Québec; Genome British Columbia; Institute of Genetics; National Institutes of Health; Institute of Infection and Immunity; Government of Canada; Canadian Institutes of Health Research; Alliance de recherche numérique du Canada; Genome Canada; Doris Duke Charitable Foundation","keywords":"Annotation; Metabolite; Computational biology; KEGG; Genome; Metabolomics; Biology; Genome-wide association study; Genetic association; Identification (biology); Gene Annotation; Metric (unit); Genetics; Computer science; Gene; Bioinformatics; Gene ontology; Single-nucleotide polymorphism; Genotype; Gene expression","routes":{"ca_aff":true,"ca_fund":true,"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":[0.003472858,0.001008422,0.001066615,0.003051153,0.0006492627,0.002063333,0.0007326133,0.0006386961,0.004561957],"category_scores_gemma":[0.01447641,0.0003017097,0.001225664,0.003482589,0.0006795226,0.000956715,0.00202167,0.0008758837,0.001811424],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004287063,"about_ca_system_score_gemma":0.0006927797,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001231573,"about_ca_topic_score_gemma":0.0014034,"domain_scores_codex":[0.9964743,0.001264591,0.0003181442,0.001060505,0.0006894759,0.0001929782],"domain_scores_gemma":[0.9929206,0.004134138,0.0009261326,0.001011208,0.0007778304,0.0002302242],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.003265956,0.0004732906,0.2925883,0.004033027,0.002382142,0.003003439,0.001873981,0.09251578,0.3354345,0.02230576,0.009194319,0.2329295],"study_design_scores_gemma":[0.0002696495,0.0006177386,0.2243489,0.0002948768,0.0009892333,0.002734328,0.001107631,0.4278247,0.1912073,0.08340682,0.066765,0.0004338304],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4807691,0.001688948,0.488944,0.0005808006,0.0002338954,0.0001296389,0.01615768,0.005751931,0.005744122],"genre_scores_gemma":[0.6863074,0.0004712125,0.3008758,0.0001224676,0.00006888422,0.000143739,0.009812357,0.0007856716,0.001412619],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004561957,"threshold_uncertainty_score":0.01836646,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02052441701594794,"score_gpt":0.2578211766031288,"score_spread":0.2372967595871808,"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."}}