{"id":"W3109130743","doi":"10.1016/j.jinf.2020.11.031","title":"Mendelian randomization analysis identified genes pleiotropically associated with the risk and prognosis of COVID-19","year":2020,"lang":"en","type":"article","venue":"Journal of Infection","topic":"COVID-19 Clinical Research Studies","field":"Medicine","cited_by":70,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"National Institute on Aging; National Institutes of Health; China Scholarship Council; National Natural Science Foundation of China","keywords":"Mendelian randomization; Coronavirus disease 2019 (COVID-19); Pandemic; Genome-wide association study; Biology; 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Mendelian inheritance; Genetics; Disease; Genetic association; Gene; Genetic variation; Single-nucleotide polymorphism; Computational biology; Medicine; Genotype; Genetic variants; Virology; Internal medicine; Outbreak; Infectious disease (medical specialty)","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.001217484,0.00007668481,0.0004544001,0.0001918076,0.0001137312,0.00002391334,0.00004100831,0.00005871508,0.00003108909],"category_scores_gemma":[0.04370212,0.00004031896,0.0002174262,0.0009867976,0.0001190499,0.00008127539,0.00002972039,0.0003172125,3.708762e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009577072,"about_ca_system_score_gemma":0.0002083752,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001532494,"about_ca_topic_score_gemma":0.0001404184,"domain_scores_codex":[0.9984728,0.0003632677,0.0004675647,0.0001090408,0.0004917569,0.00009561762],"domain_scores_gemma":[0.9957655,0.002596177,0.0007280491,0.00006634354,0.00067095,0.000172979],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002231732,0.0001046423,0.9846767,0.0001224642,0.003738273,0.00001587528,0.0004327359,0.004956788,0.001175621,0.000005086866,0.000776535,0.001763549],"study_design_scores_gemma":[0.009398249,0.00207264,0.9713918,0.00005573177,0.005992152,0.000004332133,0.0000991334,0.008209716,0.0008292383,0.00007014128,0.001804677,0.00007221528],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8622226,0.0001103574,0.0644602,0.07288162,0.00002073376,0.0002786199,0.000003960125,0.00001248509,0.000009470441],"genre_scores_gemma":[0.9954485,0.001441248,0.00008844577,0.002873431,0.0001222984,0.000005373263,0.000002736483,0.00000569534,0.0000123057],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1332259,"threshold_uncertainty_score":0.9643532,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04313554901540242,"score_gpt":0.378828577093397,"score_spread":0.3356930280779946,"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."}}