{"id":"W2954632147","doi":"10.1503/jpn.180016","title":"An artificial neural network model for clinical score prediction in Alzheimer disease using structural neuroimaging measures","year":2019,"lang":"en","type":"article","venue":"Journal of Psychiatry and Neuroscience","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Douglas Mental Health University Institute; University of Toronto; Centre for Addiction and Mental Health","funders":"National Institute of Mental Health; National Institute on Aging","keywords":"Neuroimaging; Alzheimer's Disease Neuroimaging Initiative; Alzheimer's disease; Disease; Dementia; Correlation; Mini–Mental State Examination; Psychology; Medicine; Neuroscience; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.003695965,0.001738897,0.001119802,0.0009421459,0.00053782,0.00104584,0.001715796,0.001818769,0.00172108],"category_scores_gemma":[0.006854478,0.0006414558,0.0009715136,0.0006655082,0.0007448196,0.0009207561,0.0009342569,0.002108209,0.0003995744],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001481218,"about_ca_system_score_gemma":0.001073582,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0178663,"about_ca_topic_score_gemma":0.01074686,"domain_scores_codex":[0.9991935,0.0003763097,0.00004849556,0.0002144578,0.00008730525,0.00007999113],"domain_scores_gemma":[0.9961513,0.002753006,0.0002620555,0.00009450114,0.000646291,0.00009289365],"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":[0.0001665147,0.00009147629,0.003271395,0.00002837354,0.00007067912,0.00006023228,0.00003900112,0.9821729,0.0003248016,0.0005450087,0.0004690047,0.01276066],"study_design_scores_gemma":[0.000005628508,0.00001414123,0.0002688093,0.00000338389,0.00000593821,0.000004579023,0.000002231588,0.9992008,0.00004339524,0.0004229786,0.00002537305,0.000002770104],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.571079,0.002537204,0.4167471,0.002348362,0.000319676,0.000336788,0.001536848,0.0009283605,0.004166565],"genre_scores_gemma":[0.9652959,0.0002917956,0.0304235,0.0002385628,0.00007431507,0.000409671,0.0009086237,0.00002535368,0.00233223],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0178663,"threshold_uncertainty_score":0.03552467,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1421427235151553,"score_gpt":0.425465808797042,"score_spread":0.2833230852818867,"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."}}