{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004821525,0.0009138506,0.0006313127,0.002840182,0.0005278607,0.000720031,0.0009244714,0.001053705,0.001830016],"category_scores_gemma":[0.00264657,0.0004302209,0.000735643,0.0009056958,0.000522362,0.001010108,0.0007255739,0.0004471792,0.0005258331],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000977709,"about_ca_system_score_gemma":0.001149676,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009133756,"about_ca_topic_score_gemma":0.01599574,"domain_scores_codex":[0.9994205,0.00008386734,0.00002688544,0.0001435149,0.0002777598,0.00004743316],"domain_scores_gemma":[0.9989997,0.0004037599,0.0002079442,0.00009691568,0.0002393693,0.00005233781],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003140409,0.0001770813,0.01643632,0.0003417803,0.0002269475,0.0009239545,0.0001265822,0.3110154,0.05438229,0.003511657,0.01158536,0.6009585],"study_design_scores_gemma":[0.00001317686,0.00006085353,0.007220608,0.0000208234,0.00002980386,0.0003045002,0.00003534008,0.9724193,0.01403509,0.003562685,0.002277753,0.00002007374],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3549085,0.003714246,0.62414,0.001829554,0.0002335562,0.0003778034,0.002200607,0.00876394,0.003831885],"genre_scores_gemma":[0.747533,0.001344868,0.2438381,0.0002651276,0.0002396793,0.0002187078,0.002995213,0.0004665907,0.003098746],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009133756,"threshold_uncertainty_score":0.01816118,"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."}}