{"id":"W4395067675","doi":"10.59275/j.melba.2024-4dg2","title":"A voxel-level approach to brain age prediction: A method to assess regional brain aging","year":2024,"lang":"en","type":"article","venue":"The Journal of Machine Learning for Biomedical Imaging","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hotchkiss Brain Institute; Ontario Brain Institute; University of Calgary","funders":"","keywords":"Brain aging; Voxel; Aging brain; Computer science; Psychology; Artificial intelligence; Neuroscience; Cognition","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"],"consensus_categories":[],"category_scores_codex":[0.007706529,0.0002650066,0.0003842584,0.0006679558,0.0006095474,0.000237028,0.0006241471,0.00005025982,0.0000214481],"category_scores_gemma":[0.0256799,0.0001794889,0.000251098,0.001194578,0.0002073276,0.0003069947,0.0003204088,0.001183677,0.00001813688],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001824509,"about_ca_system_score_gemma":0.0001590516,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003162721,"about_ca_topic_score_gemma":0.000001995459,"domain_scores_codex":[0.996357,0.0009987145,0.0005824143,0.0004755415,0.001093458,0.0004928217],"domain_scores_gemma":[0.9782468,0.02092081,0.0001814717,0.0001914655,0.000132065,0.0003273963],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007081318,0.0003324092,0.0003692866,0.0003666471,0.0002804733,0.0002698354,0.008411454,0.0144299,0.3808711,0.005003381,0.4245075,0.1644499],"study_design_scores_gemma":[0.0008383807,0.0005517986,0.0009947913,0.0004628215,0.0001026037,0.003396595,0.0005612068,0.2036638,0.001816135,0.00225615,0.7850453,0.0003104634],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002485006,0.0002984795,0.7251122,0.2705115,0.0007207461,0.0002893526,0.00002975229,0.0001155959,0.0004373336],"genre_scores_gemma":[0.743803,0.00003091657,0.156943,0.08738341,0.005027778,0.0001048333,0.0000225519,0.00021877,0.006465722],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.741318,"threshold_uncertainty_score":0.9825272,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1009177687035369,"score_gpt":0.3692185245557048,"score_spread":0.2683007558521679,"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."}}