{"id":"W2910320413","doi":"10.1111/jon.12598","title":"Semiautomated Assessment of the Anterior Cingulate Cortex in Alzheimer's Disease","year":2019,"lang":"en","type":"article","venue":"Journal of Neuroimaging","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"National Institute of Biomedical Imaging and Bioengineering; Eisai Korea; National Institutes of Health; Servier; Northern California Institute for Research and Education; Natural Sciences and Engineering Research Council of Canada; GE Healthcare; BioClinica; Biogen; U.S. Department of Defense; Meso Scale Diagnostics; Alzheimer's Disease Neuroimaging Initiative; Novartis Pharmaceuticals Corporation; Pfizer; Eli Lilly and Company; Bristol-Myers Squibb; Merck; Alzheimer's Drug Discovery Foundation; Takeda Pharmaceutical Company; AbbVie; National Institute on Aging; Fujirebio Europe; Alzheimer's Association","keywords":"Medicine; Anterior cingulate cortex; Neuroimaging; Posterior cingulate; Alzheimer's disease; Magnetic resonance imaging; Segmentation; Cingulate cortex; Cognition; Disease; Internal medicine; Radiology; Psychiatry; Artificial intelligence; Central nervous system; Computer science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001579167,0.0004454253,0.0003513671,0.001258502,0.0002732187,0.0008596134,0.00079538,0.0005729022,0.001104385],"category_scores_gemma":[0.004849974,0.0004024027,0.000343043,0.0004861453,0.000372352,0.0005015191,0.0003889702,0.000336235,0.0003487759],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000377126,"about_ca_system_score_gemma":0.000560989,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002585693,"about_ca_topic_score_gemma":0.007007899,"domain_scores_codex":[0.9990156,0.0003831698,0.0001112593,0.0001525003,0.0003032373,0.00003427872],"domain_scores_gemma":[0.9979431,0.0007615059,0.0003002562,0.0003215488,0.0006301505,0.00004339944],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.002831378,0.0003650557,0.0628144,0.001259782,0.0005489251,0.0006674072,0.0009066988,0.02557092,0.4989841,0.001753576,0.003881332,0.4004164],"study_design_scores_gemma":[0.0003312085,0.001359671,0.5298235,0.000294506,0.0005322168,0.008473211,0.0004139834,0.215319,0.2278961,0.004042387,0.01113474,0.0003792558],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.6805673,0.0043101,0.3084822,0.000202153,0.0001603757,0.0008574454,0.001147634,0.001424704,0.00284808],"genre_scores_gemma":[0.6641936,0.0006741607,0.3319639,0.0001142417,0.00005004214,0.0005619664,0.001025695,0.0001928716,0.001223485],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.002585693,"threshold_uncertainty_score":0.008351505,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01563428993987858,"score_gpt":0.3440485773556085,"score_spread":0.3284142874157299,"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."}}