{"id":"W4366588666","doi":"10.3174/ajnr.a7845","title":"3D Capsule Networks for Brain Image Segmentation","year":2023,"lang":"en","type":"article","venue":"American Journal of Neuroradiology","topic":"Medical Image Segmentation Techniques","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre for Advancing Health Outcomes","funders":"National Center for Advancing Translational Sciences; Engineering and Physical Sciences Research Council; RSNA Research and Education Foundation; Radiological Society of North America; Yale University; National Institutes of Health; Alzheimer's Disease Neuroimaging Initiative","keywords":"Medicine; Capsule; Artificial intelligence; Segmentation; Computer vision; Anatomy; Pattern recognition (psychology); Computer science; Paleontology; Geology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007017405,0.00009857037,0.000282553,0.0002514955,0.00005857775,0.00004249504,0.0005972873,0.00002693945,0.00001029638],"category_scores_gemma":[0.0005123108,0.0000868081,0.00009177851,0.0006367742,0.0002333656,0.0003407258,0.0000690347,0.0001752093,0.00001024852],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003188549,"about_ca_system_score_gemma":0.00006304363,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005522732,"about_ca_topic_score_gemma":3.568584e-7,"domain_scores_codex":[0.9986585,0.0002936323,0.0004266591,0.0001843889,0.0001687393,0.0002680872],"domain_scores_gemma":[0.9982259,0.0007668504,0.0005254946,0.0001960657,0.0001547845,0.0001309547],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000380783,0.0000492031,0.0002504533,0.00001116146,0.00005681425,0.0002118781,0.0005403921,0.0007486519,0.127499,0.0006431992,0.1617955,0.7081557],"study_design_scores_gemma":[0.009162499,0.03891084,0.03755525,0.0001723611,0.0001907636,0.008211439,0.001888045,0.7153863,0.1414765,0.01215434,0.03269562,0.00219602],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02115607,0.00001401414,0.9717621,0.006300484,0.0004838641,0.0001369946,0.000001895069,0.000116114,0.0000285107],"genre_scores_gemma":[0.1458654,0.0001600626,0.8390523,0.01425517,0.00048106,0.00003698115,0.00001223249,0.00003150377,0.0001053204],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7146377,"threshold_uncertainty_score":0.3539932,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0151102763025504,"score_gpt":0.3130004469947647,"score_spread":0.2978901706922143,"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."}}