{"id":"W3195419882","doi":"10.1109/rbme.2021.3107372","title":"A Review of Neuroimaging-Driven Brain Age Estimation for Identification of Brain Disorders and Health Conditions","year":2021,"lang":"en","type":"review","venue":"IEEE Reviews in Biomedical Engineering","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":98,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Neuroimaging; Estimation; Brain aging; Identification (biology); Brain morphometry; Medicine; Neuroscience; Computer science; Psychology; Cognition; Magnetic resonance imaging; Biology; Radiology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002046289,0.0003227584,0.002404557,0.0004046758,0.00005016028,0.00001309185,0.0002339012,0.0001038584,0.000005969556],"category_scores_gemma":[0.03132666,0.0002959089,0.0003997925,0.001213672,0.0001932929,0.0001046948,0.0000739319,0.0002883348,0.000002114367],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001222948,"about_ca_system_score_gemma":0.0001838508,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007373916,"about_ca_topic_score_gemma":0.000004164347,"domain_scores_codex":[0.996582,0.0003940214,0.001886652,0.0006058959,0.0002816452,0.0002497474],"domain_scores_gemma":[0.9921008,0.006457635,0.0009350657,0.0003734365,0.00003932305,0.0000937934],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[3.625923e-7,0.00006766924,2.496746e-7,0.3876231,0.00001692046,0.000001759902,0.00002821313,0.00004136543,0.0002147392,0.0004807869,0.009650976,0.6018739],"study_design_scores_gemma":[0.0001189999,0.000047084,0.000004592296,0.1852692,0.00007337784,0.00002035243,0.000001230969,0.002240086,0.000008494932,0.0000386441,0.812007,0.0001709917],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[8.048142e-7,0.9734596,0.01889338,0.00455255,0.0004481194,0.002411499,0.0002025222,0.00002756991,0.00000393878],"genre_scores_gemma":[0.00001041367,0.9968575,0.001057095,0.001138158,0.00004973413,0.0006867382,0.0001481313,0.00003885639,0.00001332061],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.802356,"threshold_uncertainty_score":0.9999493,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09143183144687225,"score_gpt":0.4002574448941021,"score_spread":0.3088256134472298,"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."}}