{"id":"W2079225159","doi":"10.1016/j.neuroimage.2010.09.071","title":"Correlation between baseline regional gray matter volume and global gray matter volume decline rate","year":2010,"lang":"en","type":"article","venue":"NeuroImage","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"National Cancer Institute; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Institute on Drug Abuse; Ministry of Education, Culture, Sports, Science and Technology; Japan Society for the Promotion of Science; Canadian Institutes of Health Research; Tohoku University","keywords":"Precuneus; Gray (unit); Magnetic resonance imaging; Brain size; Voxel-based morphometry; Correlation; Grey matter; Psychology; Cardiology; Internal medicine; Medicine; Neuroscience; White matter; Cognition; Nuclear medicine; Radiology; Mathematics","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":[],"consensus_categories":[],"category_scores_codex":[0.0009561887,0.0002199532,0.0005493973,0.0007325505,0.0002011637,0.0004894653,0.0002474472,0.0004551224,0.002456509],"category_scores_gemma":[0.004155563,0.000196198,0.0002947828,0.0003444648,0.0002348609,0.0005801628,0.0002390339,0.0006238674,0.0003653181],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002093495,"about_ca_system_score_gemma":0.0002658219,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002673864,"about_ca_topic_score_gemma":0.002540743,"domain_scores_codex":[0.9997852,0.00004108803,0.00002751641,0.00006660042,0.00004442463,0.00003514606],"domain_scores_gemma":[0.9975122,0.0009942999,0.0006564996,0.0002311728,0.0003572732,0.0002485398],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002284904,0.0001638964,0.9873455,0.00002235711,0.00019545,0.0001839378,0.00009379717,0.0002658191,0.00349143,0.00005169914,0.0001624507,0.005738758],"study_design_scores_gemma":[0.000009641984,0.0003024708,0.9984673,0.000001795445,0.00003701749,0.0003424195,0.00002869503,0.0003868185,0.0002893343,0.00006573297,0.00006474264,0.000004052481],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9981005,0.0002788498,0.0002351273,0.00003769571,0.000008624203,0.000009879685,0.0002776663,0.00002215826,0.001029518],"genre_scores_gemma":[0.9987664,0.00009816066,0.0001833368,0.00001401456,0.00001208744,0.0000092801,0.0003262497,0.00000676021,0.0005836532],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002673864,"threshold_uncertainty_score":0.008217871,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0161827356199979,"score_gpt":0.2979921714766873,"score_spread":0.2818094358566894,"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."}}