{"id":"W4416067797","doi":"10.3390/cells14221754","title":"Three-Dimensional PET Imaging Reveals Canal-like Networks for Amyloid Beta Clearance to the Peripheral Lymphatic System","year":2025,"lang":"en","type":"article","venue":"Cells","topic":"Dementia and Cognitive Impairment Research","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"School of Veterinary Medicine, Ross University; National Institute of Biomedical Imaging and Bioengineering; National Institute on Aging; Canadian Institutes of Health Research; IXICO; Genentech; Pfizer; Novartis Pharmaceuticals Corporation; F. Hoffmann-La Roche; Biogen; Merck; Servier; GE Healthcare; BioClinica; Eli Lilly and Company; Foundation for the National Institutes of Health","keywords":"Context (archaeology); Visualization; Magnetic resonance imaging; Neuroimaging; SIGNAL (programming language); Functional imaging; Skull; Positron emission tomography","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":[0.0002419279,0.0002128062,0.0001619471,0.0005467927,0.0001550146,0.0007487212,0.0001992867,0.0003712711,0.001275853],"category_scores_gemma":[0.0004192746,0.000253494,0.0002052429,0.0003394627,0.0002177501,0.0003926212,0.0002519024,0.0002545284,0.0003559683],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002023008,"about_ca_system_score_gemma":0.0002782508,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0015456,"about_ca_topic_score_gemma":0.001681697,"domain_scores_codex":[0.9999421,0.00001018375,0.000003742235,0.00001639135,0.00001503936,0.00001260702],"domain_scores_gemma":[0.9998773,0.00003495095,0.00002639162,0.00002043416,0.00002649823,0.00001441518],"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":[0.0006002933,0.00007114468,0.03453197,0.0002408571,0.00008846568,0.001909441,0.0005376023,0.01307176,0.9022327,0.001732337,0.00111825,0.04386512],"study_design_scores_gemma":[0.00008638466,0.0005375742,0.3201275,0.0001022391,0.0002595065,0.01109451,0.000970059,0.1891547,0.4542439,0.005850193,0.01735787,0.0002156989],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9564289,0.0006370074,0.04051093,0.0001265215,0.00001347281,0.00002942788,0.0006329124,0.0003157541,0.001305088],"genre_scores_gemma":[0.9789327,0.0004970458,0.01916924,0.00004612231,0.000008429687,0.00003576184,0.000494602,0.00005593834,0.0007602874],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0015456,"threshold_uncertainty_score":0.004268229,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009408623041708156,"score_gpt":0.2770411388395115,"score_spread":0.2676325157978034,"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."}}