{"id":"W3010298166","doi":"10.3233/jad-190706","title":"Improving Choroid Plexus Segmentation in the Healthy and Diseased Brain: Relevance for Tau-PET Imaging in Dementia","year":2020,"lang":"en","type":"article","venue":"Journal of Alzheimer s Disease","topic":"Cerebrospinal fluid and hydrocephalus","field":"Neuroscience","cited_by":94,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; NIH Office of the Director; National Institute of Mental Health; National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; Advanced Research Projects Agency; Genentech; Defense Advanced Research Projects Agency; National Institutes of Health; National Institute of Neurological Disorders and Stroke; Intelligence Advanced Research Projects Activity; IXICO; H. Lundbeck A/S; Servier; Eisai; Office of the Director of National Intelligence; Northern California Institute for Research and Education; Pfizer; Biogen; BioClinica; Harvard Catalyst; University of Southern California; Novartis Pharmaceuticals Corporation; Alzheimer's Association; Beth Israel Deaconess Medical Center; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Foundation for the National Institutes of Health; Harvard University; National Center for Research Resources; F. Hoffmann-La Roche; Sidney R. Baer, Jr. Foundation; Alzheimer's Disease Neuroimaging Initiative; National Center for Advancing Translational Sciences; Meso Scale Diagnostics","keywords":"Choroid plexus; Dementia; Neuroscience; Pet imaging; Plexus; Medicine; Relevance (law); Neuroimaging; Segmentation; Psychology; Positron emission tomography; Anatomy; Pathology; Central nervous system; Computer science; Artificial intelligence; Disease","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":[0.002751507,0.001788492,0.001307935,0.002563567,0.00107284,0.002056003,0.0008863892,0.001959663,0.0008466069],"category_scores_gemma":[0.007053352,0.0007879483,0.001173614,0.001148585,0.0008310498,0.001362004,0.001209462,0.0008320616,0.0007011126],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001007438,"about_ca_system_score_gemma":0.00165757,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01402393,"about_ca_topic_score_gemma":0.01918036,"domain_scores_codex":[0.9991075,0.0003293458,0.00005839046,0.0002764254,0.000119579,0.0001087078],"domain_scores_gemma":[0.9986657,0.0006125318,0.000146769,0.0002149698,0.0002551281,0.0001048874],"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":[0.002022483,0.0002614288,0.04331969,0.001070887,0.0008492059,0.0009374545,0.000980725,0.07587872,0.2528791,0.003053779,0.006706695,0.6120397],"study_design_scores_gemma":[0.0001458671,0.0004740015,0.06450806,0.0002427462,0.0005871101,0.002723464,0.000765542,0.7731218,0.1339625,0.01379846,0.009456802,0.0002136175],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4314219,0.009028001,0.5455911,0.001735349,0.0002740372,0.000370889,0.001182109,0.008391397,0.002005353],"genre_scores_gemma":[0.5739548,0.002527053,0.419618,0.0002689867,0.0001203734,0.0001351497,0.001384498,0.000838053,0.001153077],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01402393,"threshold_uncertainty_score":0.0278846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03387515599760024,"score_gpt":0.3018420426675043,"score_spread":0.2679668866699041,"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."}}