{"id":"W4404195865","doi":"10.1002/alz.14319","title":"Assessing polyomic risk to predict Alzheimer's disease using a machine learning model","year":2024,"lang":"en","type":"article","venue":"Alzheimer s & Dementia","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"National Institute of General Medical Sciences; National Institutes of Health; Cure Alzheimer's Fund","keywords":"Disease; Artificial intelligence; Machine learning; Computer science; Medicine; Psychology; Internal medicine","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":[0.00263908,0.001287588,0.0008746252,0.001867726,0.0004269386,0.001102302,0.0007123988,0.0009621754,0.002142988],"category_scores_gemma":[0.005483787,0.0002436551,0.001414702,0.0008643944,0.000409271,0.0006203573,0.000733367,0.001330712,0.0007124501],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007035512,"about_ca_system_score_gemma":0.001069959,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008894041,"about_ca_topic_score_gemma":0.004930503,"domain_scores_codex":[0.9992833,0.0002771869,0.00006022716,0.0002110408,0.00006917529,0.00009908855],"domain_scores_gemma":[0.9965104,0.00249012,0.000280449,0.0001686707,0.0003963808,0.0001539286],"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":[0.001003443,0.0007794213,0.235542,0.0001410893,0.001037291,0.0004086924,0.0001437989,0.6393142,0.00251606,0.001392577,0.004687552,0.1130339],"study_design_scores_gemma":[0.0000110751,0.00009325038,0.005512529,0.00001537929,0.00005115599,0.00004466958,0.00001401974,0.9924522,0.0001866936,0.001408634,0.0002010422,0.000009349619],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7477638,0.001576468,0.2422584,0.001913951,0.0002005521,0.0002252504,0.002663808,0.001316611,0.002081157],"genre_scores_gemma":[0.9735528,0.0002339029,0.02320054,0.0002251152,0.00006524863,0.0001264652,0.001507696,0.00003373401,0.001054619],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008894041,"threshold_uncertainty_score":0.01768452,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05026165900259608,"score_gpt":0.3582284915697359,"score_spread":0.3079668325671397,"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."}}