{"id":"W4205249103","doi":"10.34133/2022/9783128","title":"Automated Segmentation and Connectivity Analysis for Normal Pressure Hydrocephalus","year":2022,"lang":"en","type":"article","venue":"BME Frontiers","topic":"Cerebrospinal fluid and hydrocephalus","field":"Neuroscience","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Janssen Alzheimer Immunotherapy Research And Development; National Institute on Aging; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; Northern California Institute for Research and Education; Alzheimer's Disease Neuroimaging Initiative; GE Healthcare; Pfizer; Biogen; BioClinica; F. Hoffmann-La Roche; University of Southern California; Novartis Pharmaceuticals Corporation; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; Foundation for the National Institutes of Health; Meso Scale Diagnostics; Alzheimer's Association; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; National Science Foundation","keywords":"Computer science; Normal pressure hydrocephalus; Segmentation; Artificial intelligence; Connectomics; Hausdorff distance; Pattern recognition (psychology); Diffusion MRI; Third ventricle; Magnetic resonance imaging; Connectome; Radiology; Medicine; Neuroscience","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":[0.0002081602,0.000131757,0.0002321823,0.000213323,0.0006257357,0.00005835192,0.0001559221,0.00003153253,0.000127209],"category_scores_gemma":[0.00009920492,0.000142991,0.0001175213,0.0006076631,0.0000634879,0.0002108526,0.000111424,0.0001004748,0.00000205278],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006349307,"about_ca_system_score_gemma":0.0000345576,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005330427,"about_ca_topic_score_gemma":0.00001039722,"domain_scores_codex":[0.9987215,0.0001130889,0.000168144,0.0004464563,0.0002757885,0.0002750421],"domain_scores_gemma":[0.9995807,0.00006635637,0.00009274015,0.0001522144,0.0000191088,0.00008891272],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002461104,0.0009538253,0.1974549,0.0003253284,0.001685074,0.00005913173,0.005305258,0.1309939,0.521242,0.003332392,0.1244678,0.01171929],"study_design_scores_gemma":[0.00179952,0.000403144,0.03255157,0.00000177328,0.0008825552,0.00002789905,0.0005178277,0.9148126,0.02853528,0.0003898573,0.01968903,0.0003890028],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9796223,0.0004106655,0.01699919,0.0002686632,0.0005972271,0.0006808575,0.0003391887,0.0003845048,0.0006973901],"genre_scores_gemma":[0.9973499,0.00001227345,0.0006466282,0.0003573075,0.00003936487,0.000182244,0.00003410136,0.00001610313,0.001362088],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7838186,"threshold_uncertainty_score":0.5831006,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01594734154944697,"score_gpt":0.2591425472621471,"score_spread":0.2431952057127002,"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."}}