{"id":"W4362469863","doi":"10.3390/genes14040834","title":"Gene Association Analysis of Quantitative Trait Based on Functional Linear Regression Model with Local Sparse Estimator","year":2023,"lang":"en","type":"article","venue":"Genes","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Simon Fraser University; National Natural Science Foundation of China","keywords":"Linkage disequilibrium; Genetic association; Association mapping; Regression analysis; Computer science; Estimator; Regression; Linear regression; Linear model; Quantitative trait locus; Statistics; Data mining; Single-nucleotide polymorphism; Pattern recognition (psychology); Genetics; Mathematics; Biology; Artificial intelligence; Gene; Machine learning","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004132694,0.000608907,0.001272437,0.001132108,0.0003312395,0.0006047131,0.001235,0.0007439584,0.001322036],"category_scores_gemma":[0.01022792,0.0003027199,0.0011933,0.001244035,0.0008345283,0.0009486077,0.0007869825,0.0009190558,0.0002418604],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004617801,"about_ca_system_score_gemma":0.0009412778,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005440057,"about_ca_topic_score_gemma":0.003929261,"domain_scores_codex":[0.9972501,0.001480049,0.00008811324,0.0006924069,0.0003363306,0.0001529687],"domain_scores_gemma":[0.9939452,0.00468192,0.0005249631,0.0003288405,0.0004172371,0.0001018692],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004765882,0.0001809484,0.05875317,0.0004590163,0.0007642542,0.0006277342,0.0003191707,0.6474758,0.01066588,0.04135424,0.002042065,0.2368811],"study_design_scores_gemma":[0.0000181948,0.00005222607,0.002802619,0.000006889178,0.00003855289,0.00008777673,0.00001601579,0.990458,0.0004886399,0.005708634,0.0003082266,0.00001408795],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03122019,0.0001729272,0.9679391,0.0001115104,0.00001350667,0.00002536776,0.0001038798,0.0001871559,0.0002262818],"genre_scores_gemma":[0.756199,0.0005043612,0.2401876,0.0001669638,0.00009294346,0.0002494227,0.0008280264,0.00006325609,0.001708344],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005440057,"threshold_uncertainty_score":0.02185601,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03674056660965078,"score_gpt":0.2993611199816341,"score_spread":0.2626205533719833,"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."}}