{"id":"W2998754344","doi":"10.1101/2020.01.15.907436","title":"Genetic associations at regulatory phenotypes improve fine-mapping of causal variants for twelve immune-mediated diseases","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Institutes of Health Research; National Institute for Health and Care Research; European Bioinformatics Institute","keywords":"Quantitative trait locus; Biology; Genetics; Indel; Computational biology; Major histocompatibility complex; Disease; Candidate gene; Inclusive composite interval mapping; Gene; Gene mapping; Single-nucleotide polymorphism; Medicine; Genotype","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004257527,0.0004999313,0.0008366884,0.0001184186,0.0002134546,0.00003531229,0.0005001918,0.0008651169,0.00002093431],"category_scores_gemma":[0.002248169,0.0005694332,0.0003955804,0.0002149099,0.0001371289,0.00000591487,0.0007396416,0.0002708111,0.00001455715],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002206843,"about_ca_system_score_gemma":0.0008825018,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005663987,"about_ca_topic_score_gemma":0.00001074647,"domain_scores_codex":[0.9969666,0.0002218578,0.0009567384,0.001044943,0.0002295418,0.0005802963],"domain_scores_gemma":[0.9966992,0.0001623862,0.001186665,0.001023022,0.0006800288,0.0002486971],"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":[0.00004948771,0.0001064742,0.04791343,0.0002185472,0.0007000029,0.000002590797,0.00001389303,0.0002925702,0.9488177,0.00006928873,0.001813017,0.000003039777],"study_design_scores_gemma":[0.0009492117,0.0001679009,0.9170561,0.00007204892,0.0003643744,1.277741e-8,0.000006716042,0.0009663701,0.07760132,0.00002198252,0.002085099,0.000708894],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9818767,0.003416141,0.007138598,0.0003368991,0.000997029,0.001059687,0.005090391,0.00007833309,0.000006237522],"genre_scores_gemma":[0.9886417,0.0002599127,0.009554072,0.0001900422,0.000808762,0.0003548744,0.00005509497,0.0001197096,0.00001578684],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8712164,"threshold_uncertainty_score":0.9996757,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01365269130902163,"score_gpt":0.2282888708252112,"score_spread":0.2146361795161896,"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."}}