{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003753325,0.0001135577,0.0002374446,0.000164784,0.00007641855,0.000003496408,0.00006639925,0.0001596474,0.00001727576],"category_scores_gemma":[0.000174256,0.00008990484,0.0001302556,0.0004670033,0.0000399818,0.000001870828,0.00002254582,0.00004665373,0.000009339351],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003151597,"about_ca_system_score_gemma":0.000104337,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000267145,"about_ca_topic_score_gemma":0.00006815933,"domain_scores_codex":[0.9990582,0.00009283155,0.0002139713,0.0002677736,0.0001875368,0.0001797072],"domain_scores_gemma":[0.9992944,0.00008305607,0.0002100647,0.0001884311,0.0001797098,0.00004433059],"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":[0.000129175,0.00004408231,0.04550109,0.000004377848,0.0003960058,6.306682e-7,0.00001814272,0.9165969,0.03507313,0.00003934855,0.0015583,0.0006388514],"study_design_scores_gemma":[0.0003288801,0.0002379276,0.1484735,0.000005362761,0.0002456807,2.175967e-7,0.00007079511,0.8376943,0.01262633,0.00003598227,0.0001796509,0.000101389],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8097647,0.00005261236,0.1894802,0.0003140518,0.00004402066,0.00006843863,0.0001748164,0.00001429403,0.00008681841],"genre_scores_gemma":[0.98097,0.00003492023,0.01678087,0.000145017,0.0000431331,0.00002439542,0.001481783,0.00001339431,0.0005064756],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1726994,"threshold_uncertainty_score":0.3666213,"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."}}