{"id":"W4390717645","doi":"10.1212/nxg.0000000000200120","title":"Machine Learning Models of Polygenic Risk for Enhanced Prediction of Alzheimer Disease Endophenotypes","year":2024,"lang":"en","type":"article","venue":"Neurology Genetics","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Canadian Institutes of Health Research; GHR Foundation; Northern California Institute for Research and Education; Pfizer; Novartis Pharmaceuticals Corporation; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; Avid Radiopharmaceuticals; Mayo Foundation for Medical Education and Research; Regeneron Pharmaceuticals; BioClinica; Mayo Clinic; Biogen; Bristol-Myers Squibb; Eli Lilly and Company","keywords":"Endophenotype; Dementia; Genome-wide association study; Neuroimaging; Disease; Medicine; Genetic architecture; Psychology; Internal medicine; Cognition; Biology; Single-nucleotide polymorphism; Genotype; Psychiatry; Quantitative trait locus; Genetics; Population","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":[0.0074909,0.0007582823,0.0006968048,0.0009021926,0.0003630601,0.0008186646,0.0008905915,0.0006688426,0.002543055],"category_scores_gemma":[0.01303744,0.0003378903,0.001436603,0.0006452952,0.0004020967,0.0009942831,0.0006263261,0.001236907,0.0007758467],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007277764,"about_ca_system_score_gemma":0.000714528,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003471194,"about_ca_topic_score_gemma":0.004425301,"domain_scores_codex":[0.9979575,0.001370305,0.00008615696,0.0003867777,0.0001106389,0.00008871006],"domain_scores_gemma":[0.9919269,0.006639075,0.0004708678,0.0004544376,0.0004010815,0.0001075846],"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":[0.0008088552,0.0004624587,0.1166091,0.00023224,0.001445358,0.0002161363,0.0001965006,0.6701481,0.002435897,0.004358266,0.004266149,0.1988209],"study_design_scores_gemma":[0.00002372546,0.00007022498,0.00920462,0.00001893616,0.00005843672,0.00005016169,0.0000072643,0.9854904,0.0002398523,0.004496071,0.0003295737,0.00001062052],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4940375,0.002070969,0.4964866,0.002296532,0.0001394804,0.0001290709,0.001138725,0.001521809,0.002179256],"genre_scores_gemma":[0.9471195,0.0002238632,0.04935556,0.0002913462,0.0001013873,0.0001122157,0.0008812708,0.00005649513,0.001858387],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0074909,"threshold_uncertainty_score":0.03961617,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02044579922958576,"score_gpt":0.2582801765647226,"score_spread":0.2378343773351369,"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."}}