{"id":"W3209053433","doi":"10.21203/rs.3.rs-978033/v1","title":"Enhancer Promoter Interactome and Mendelian Randomization Identify Network of Druggable Vascular Genes in Coronary Artery Disease","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval; Institut universitaire de cardiologie et de pneumologie de Québec","funders":"Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research; Institut universitaire de cardiologie et de pneumologie de Québec, Université Laval","keywords":"Druggability; Mendelian randomization; Interactome; Gene; Enhancer; Computational biology; Biology; Disease; Coronary artery disease; Genetics; Bioinformatics; Medicine; Gene expression; Genetic variants; Internal medicine","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":[0.001188307,0.0002850129,0.0005620637,0.001634257,0.0002835387,0.0006382372,0.000517164,0.0005149495,0.007782005],"category_scores_gemma":[0.007369847,0.0002828219,0.0008673746,0.001131248,0.0003240946,0.0005809369,0.0004814797,0.0004961681,0.0005292353],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002312234,"about_ca_system_score_gemma":0.000404053,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001178342,"about_ca_topic_score_gemma":0.001010573,"domain_scores_codex":[0.9990202,0.0003670182,0.00003684289,0.0003801699,0.0001023874,0.00009340049],"domain_scores_gemma":[0.9950594,0.003458865,0.0006052994,0.0005050853,0.0001370059,0.0002343346],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003953287,0.0003730668,0.7678206,0.0003472533,0.002161079,0.002751858,0.0003616512,0.01467951,0.07188903,0.03957886,0.005072808,0.09101105],"study_design_scores_gemma":[0.0005153385,0.0003600136,0.713854,0.00004997839,0.001954956,0.005215238,0.0001977042,0.1323138,0.0108027,0.1284059,0.006255246,0.00007508807],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9275461,0.0008278223,0.06139463,0.0008031307,0.00004419298,0.00004079955,0.006201173,0.0003998362,0.002742281],"genre_scores_gemma":[0.9855692,0.0002425391,0.009874638,0.0001002726,0.00005961695,0.00005615795,0.002515416,0.00006953588,0.001512713],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007782005,"threshold_uncertainty_score":0.0260334,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02706093217225247,"score_gpt":0.3622837167037731,"score_spread":0.3352227845315207,"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."}}