{"id":"W3038507145","doi":"10.48550/arxiv.2007.01516","title":"Deep interpretability for GWAS","year":2020,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Interpretability; Genome-wide association study; Genetic association; Artificial intelligence; Computer science; Machine learning; Deep learning; Genetic variants; Computational biology; Association (psychology); Linear model; Data mining; Biology; Genetics; Gene; Single-nucleotide polymorphism; Psychology; Genotype","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004953243,0.001336969,0.001185192,0.001735999,0.0006248981,0.002706153,0.001860256,0.001829128,0.007999467],"category_scores_gemma":[0.0386269,0.0007423593,0.001314268,0.001173189,0.002556666,0.003903338,0.003761122,0.00516969,0.001292713],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001786951,"about_ca_system_score_gemma":0.001347904,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003068454,"about_ca_topic_score_gemma":0.002857864,"domain_scores_codex":[0.997364,0.001276409,0.000171063,0.000472027,0.0005727534,0.0001437739],"domain_scores_gemma":[0.9865262,0.009087788,0.000895398,0.002057067,0.001097802,0.0003356313],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004011005,0.0001340517,0.00620846,0.0004783069,0.0001966745,0.0007445368,0.0005722278,0.1438465,0.004142757,0.5563154,0.02065002,0.2663101],"study_design_scores_gemma":[0.00002628643,0.00002371897,0.0005513375,0.00005507862,0.00001700483,0.0000829541,0.00002515332,0.341557,0.0009551862,0.6526188,0.004073444,0.00001414895],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009482264,0.0008339463,0.9808282,0.003228939,0.0001448235,0.00005296805,0.0006893058,0.00150098,0.003238681],"genre_scores_gemma":[0.5394856,0.001722849,0.4402546,0.002590117,0.0008532312,0.0005177347,0.003316719,0.001281735,0.009977257],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007999467,"threshold_uncertainty_score":0.02676094,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06283251485236818,"score_gpt":0.2149882197980486,"score_spread":0.1521557049456805,"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."}}