{"id":"W2759802189","doi":"10.1093/hmg/ddy091","title":"Leveraging lung tissue transcriptome to uncover candidate causal genes in COPD genetic associations","year":2018,"lang":"en","type":"article","venue":"Human Molecular Genetics","topic":"Chronic Obstructive Pulmonary Disease (COPD) Research","field":"Medicine","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; St. Paul's Hospital; Université Laval; Institut universitaire de cardiologie et de pneumologie de Québec","funders":"National Heart, Lung, and Blood Institute; University of British Columbia; National Natural Science Foundation of China; Rijksuniversiteit Groningen; Canadian Institutes of Health Research; Université Laval","keywords":"Genome-wide association study; Expression quantitative trait loci; Candidate gene; Biology; Mendelian randomization; Genetics; Genetic association; COPD; Quantitative trait locus; Computational biology; Gene; Single-nucleotide polymorphism; Genotype; Medicine; Genetic variants","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001671575,0.0002799305,0.0003605406,0.0003713248,0.0001882834,0.00006179094,0.0002446376,0.0001315805,0.000562474],"category_scores_gemma":[0.00004203463,0.0003212835,0.00009727304,0.0005419898,0.0001622249,0.00003838984,0.0001257174,0.0002532205,0.0001497708],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007315791,"about_ca_system_score_gemma":0.0003656023,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003245914,"about_ca_topic_score_gemma":0.0005221433,"domain_scores_codex":[0.9974188,0.000139086,0.0004158102,0.0005934186,0.0007062103,0.0007266712],"domain_scores_gemma":[0.9985988,0.00002038946,0.00006177706,0.0006170183,0.0002788325,0.0004232558],"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":[0.00007588419,0.0002911276,0.1701481,0.000226065,0.0002197428,0.001159377,0.002501451,0.0008272803,0.8176193,0.0001724835,0.001874783,0.00488435],"study_design_scores_gemma":[0.00183669,0.0002507033,0.9556918,0.00009388015,0.0001684591,0.00003504074,0.0001349876,0.001375256,0.03258836,0.0003388381,0.007081375,0.0004046493],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9906421,0.003227786,0.002753604,0.0003894574,0.0001801909,0.001001753,0.00006622922,0.00005121181,0.001687713],"genre_scores_gemma":[0.9955975,0.0000520044,0.002021451,0.0007396605,0.0003303632,0.00006345888,0.0001082113,0.00009309285,0.0009942972],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7855436,"threshold_uncertainty_score":0.9999239,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02031776602688865,"score_gpt":0.3266496963494239,"score_spread":0.3063319303225353,"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."}}