{"id":"W4411505258","doi":"10.1007/978-3-031-95911-0_12","title":"FAST-AID Brain: Fast and Accurate Segmentation Tool Using Artificial Intelligence Developed for Brain","year":2025,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Canadian Institutes of Health Research; National Institutes of Health; Genentech; IXICO; H. Lundbeck A/S; Servier; Eisai; National Research Foundation; Northern California Institute for Research and Education; Velux Fonden; BioClinica; Biogen; Pfizer; Novartis Pharmaceuticals Corporation; University of Southern California; Danmarks Grundforskningsfond; U.S. Department of Defense; Eli Lilly and Company; Bristol-Myers Squibb; European Commission; Alzheimer's Disease Neuroimaging Initiative; Meso Scale Diagnostics; Innovationsfonden; Alzheimer's Association","keywords":"Computer science; Artificial intelligence; Segmentation; Computer vision","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006066008,0.0004909909,0.0004241292,0.0005620093,0.0005454525,0.0006335174,0.00182008,0.0002189809,0.000004198751],"category_scores_gemma":[0.0002265179,0.0004953874,0.00008109734,0.0009579706,0.0005007853,0.0008489114,0.00116427,0.0004520284,0.000005951133],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002829237,"about_ca_system_score_gemma":0.00057671,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005450847,"about_ca_topic_score_gemma":0.00005767705,"domain_scores_codex":[0.996561,0.00003619923,0.000677587,0.00164491,0.0004789268,0.0006014094],"domain_scores_gemma":[0.9967288,0.001673047,0.0003590435,0.0008334583,0.0002924292,0.0001131671],"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":[0.000007906463,0.000009845904,0.000002939814,0.00003498212,0.000005998748,0.000004874315,0.0002969255,0.09077664,0.0010286,0.08022565,0.00002204556,0.8275836],"study_design_scores_gemma":[0.00007593156,0.00005885144,0.000008713339,0.0001809751,0.00000582595,0.00002119604,6.18309e-7,0.7008739,0.004484543,0.2933318,0.0005421791,0.00041545],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0001016873,0.0001184768,0.9934694,0.003956076,0.0007907188,0.001263366,0.00001645056,0.0001347349,0.0001490981],"genre_scores_gemma":[0.009367193,0.00002259684,0.9861034,0.003805062,0.0003175933,0.00005953266,0.00001506617,0.00002773082,0.0002817948],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8271681,"threshold_uncertainty_score":0.9997498,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05292207733568615,"score_gpt":0.3234571737059674,"score_spread":0.2705350963702813,"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."}}