{"id":"W2142717410","doi":"10.1117/1.jmi.1.3.031005","title":"Magnetization-prepared rapid acquisition with gradient echo magnetic resonance imaging signal and texture features for the prediction of mild cognitive impairment to Alzheimer’s disease progression","year":2014,"lang":"en","type":"article","venue":"Journal of Medical Imaging","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute on Aging; University of California, San Diego; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; University of California, Los Angeles; National Institutes of Health; Genentech; IXICO; Servier; Instituto Tecnológico y de Estudios Superiores de Monterrey; Eisai; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; Alzheimer's Association; Amorfix Life Sciences; F. Hoffmann-La Roche; Medpace; AstraZeneca; Eli Lilly and Company; Bristol-Myers Squibb; Novartis Pharmaceuticals Corporation; Consejo Nacional de Ciencia y Tecnología; Synarc; Bayer HealthCare; Meso Scale Diagnostics; Foundation for the National Institutes of Health","keywords":"Medicine; Magnetic resonance imaging; Neuroimaging; Positron emission tomography; Logistic regression; Artificial intelligence; Cognition; Pattern recognition (psychology); Radiology; Internal medicine; Computer science; Psychiatry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00130086,0.0001617842,0.0002673184,0.0001969466,0.0001599106,0.00005740476,0.0001325113,0.00003531464,0.000182894],"category_scores_gemma":[0.0003773889,0.00009280507,0.00009677497,0.0001964796,0.0002466459,0.000159909,0.00006826173,0.0002866108,6.64311e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000380514,"about_ca_system_score_gemma":0.0002003766,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005847995,"about_ca_topic_score_gemma":0.000001046372,"domain_scores_codex":[0.9973628,0.0001447831,0.000428301,0.0002284469,0.001545994,0.0002896557],"domain_scores_gemma":[0.9980272,0.0003586813,0.0002280869,0.0001132592,0.0007408223,0.0005319276],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.005348787,0.0004486948,0.1792533,0.0001659948,0.00009531632,0.00008788129,0.000637788,0.000006154452,0.0006251727,0.00002111025,0.005637026,0.8076728],"study_design_scores_gemma":[0.008234495,0.002601725,0.9407198,0.004581537,0.001179654,0.0004076551,0.001107897,0.03746621,0.00158988,0.0001714803,0.001803622,0.0001360689],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.522195,0.1123838,0.2590942,0.09748361,0.0006599591,0.007370648,0.0001460384,0.00008280668,0.0005839323],"genre_scores_gemma":[0.9970467,0.0004352763,0.0006584156,0.00131878,0.0003908593,0.00007421103,0.00002207197,0.00002018799,0.00003350373],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8075367,"threshold_uncertainty_score":0.3784481,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01009305487226867,"score_gpt":0.3086486459863266,"score_spread":0.2985555911140579,"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."}}