{"id":"W4412825463","doi":"10.1002/hbm.70280","title":"Cross‐Dataset Evaluation of Dementia Longitudinal Progression Prediction Models","year":2025,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Mental Health; National Institute on Aging; National Medical Research Council; National Institute of Biomedical Imaging and Bioengineering; Temasek Foundation; Canadian Institutes of Health Research; Avid Radiopharmaceuticals; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Ministry of Health -Singapore; BioClinica; Biogen; Pfizer; Novartis Pharmaceuticals Corporation; University of Southern California; National Center for Advancing Translational Sciences; Meso Scale Diagnostics; Medical Research Council; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Alzheimer's Disease Neuroimaging Initiative; Alzheimer's Association","keywords":"Neuroimaging; Artificial intelligence; Computer science; Dementia; Feature (linguistics); Multivariate statistics; Recurrent neural network; Machine learning; Artificial neural network; Disease; Pattern recognition (psychology); Neuroscience; Psychology; Medicine; Pathology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.02579982,0.004323569,0.001824915,0.004194404,0.001298006,0.002471711,0.003709809,0.002829471,0.002941964],"category_scores_gemma":[0.0256999,0.0006475401,0.003387508,0.002454243,0.0009180567,0.002366269,0.002787782,0.002671224,0.002015384],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002238672,"about_ca_system_score_gemma":0.00208517,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.024534,"about_ca_topic_score_gemma":0.0302867,"domain_scores_codex":[0.9926145,0.003307246,0.0007602408,0.002077236,0.0008310939,0.0004096673],"domain_scores_gemma":[0.9868959,0.006938512,0.0008227775,0.002233854,0.00238582,0.0007232208],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.008473421,0.003840184,0.1882419,0.002850399,0.01030828,0.001077637,0.0004376913,0.3300491,0.003271425,0.002654469,0.143169,0.3056264],"study_design_scores_gemma":[0.00136682,0.002593598,0.046386,0.0005131526,0.001483766,0.0008527751,0.0003883656,0.9214849,0.004707803,0.003757926,0.01624892,0.0002160239],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8347281,0.03372353,0.04156946,0.004178614,0.003362746,0.001268367,0.05843874,0.01301557,0.009714846],"genre_scores_gemma":[0.7539345,0.00234065,0.06031608,0.001676373,0.0006339655,0.000569026,0.1742164,0.0005455163,0.005767449],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9742002,"threshold_uncertainty_score":0.1364442,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1044254687378112,"score_gpt":0.4369005414428423,"score_spread":0.3324750727050311,"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."}}