{"id":"W2058062205","doi":"10.1016/j.jalz.2013.05.051","title":"IC‐P‐055: Mixed linear longitudinal modeling of biomarkers in ADNI","year":2013,"lang":"it","type":"article","venue":"Alzheimer s & Dementia","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut Universitaire en Santé Mentale de Québec","funders":"","keywords":"Confounding; Internal medicine; Alzheimer's Disease Neuroimaging Initiative; Medicine; Random effects model; Mixed model; Oncology; Population; Alzheimer's disease; Disease; Statistics; Mathematics; Meta-analysis","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":[0.02221717,0.002414677,0.002718633,0.001828629,0.001336064,0.002937296,0.005415281,0.002283345,0.01235516],"category_scores_gemma":[0.02454863,0.00161602,0.004427338,0.001959484,0.0009889129,0.001073757,0.002690466,0.00379132,0.00241035],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001904589,"about_ca_system_score_gemma":0.004475472,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04613123,"about_ca_topic_score_gemma":0.04605795,"domain_scores_codex":[0.9929143,0.005429612,0.0001685604,0.0008585165,0.0002809271,0.0003480542],"domain_scores_gemma":[0.9922694,0.005398585,0.0004377901,0.0008191664,0.0007923922,0.0002826563],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.005502883,0.001655316,0.09545168,0.001109343,0.008453142,0.00130701,0.001316724,0.6270154,0.001662563,0.05704308,0.06504525,0.1344377],"study_design_scores_gemma":[0.0005057458,0.0006261918,0.007000193,0.0000982413,0.0005581908,0.0001745516,0.0001180116,0.9619308,0.0003778954,0.0164732,0.01204336,0.00009355273],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1332514,0.003310331,0.8238249,0.00288034,0.0009533782,0.002775215,0.021419,0.007452204,0.004133288],"genre_scores_gemma":[0.4049769,0.001209782,0.5475014,0.00100377,0.000581893,0.01129709,0.02048601,0.00101227,0.01193081],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04613123,"threshold_uncertainty_score":0.117497,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0475715515973421,"score_gpt":0.315414403604762,"score_spread":0.2678428520074199,"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."}}