{"id":"W2808442653","doi":"","title":"Deep CEST MRI: 9.4T spectral super-resolution from 3T CEST MRI data","year":2018,"lang":"de","type":"article","venue":"Max Planck Digital Library","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Tongji Medical College, Huazhong University of Science and Technology; School of Medicine, Stanford University; Centre Hospitalier Universitaire de Rennes; Feinberg School of Medicine; Southern Medical University; Max-Planck-Institut für Kognitions- und Neurowissenschaften; Huazhong University of Science and Technology; Universität Zürich; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital; Université de Montréal; Centre National de la Recherche Scientifique; Vanderbilt University; Università degli Studi di Pavia; Tongji University; Institut National de la Santé et de la Recherche Médicale; University of Toronto; Eidgenössische Technische Hochschule Zürich; Wellcome Trust; Polytechnique Montréal; University College London; King's College London; McGill University; Institut national de recherche en informatique et en automatique (INRIA); Aix-Marseille Université; Vanderbilt University Medical Center; Johns Hopkins University; Northwestern University","keywords":"Nuclear magnetic resonance; Magnetic resonance imaging; Physics; Radiology; Medicine","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","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00006352147,0.0005685726,0.0005942886,0.0001397515,0.0002968464,0.000601033,0.001280141,0.00037009,0.001508628],"category_scores_gemma":[0.00005171316,0.0005452079,0.0001352151,0.000459658,0.0005244819,0.004274034,0.001154943,0.0005864414,0.004848966],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006311491,"about_ca_system_score_gemma":0.0002105986,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005821184,"about_ca_topic_score_gemma":0.00002632245,"domain_scores_codex":[0.9966552,0.00003259506,0.0007151689,0.001292585,0.0004408949,0.0008636037],"domain_scores_gemma":[0.9966522,0.0001861362,0.000218928,0.002381567,0.00004347096,0.0005177204],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0009217257,0.001613635,0.0425686,0.0001496824,0.0002366957,0.0004692733,0.0003163179,0.00003757466,0.0006935874,0.02313601,0.9088411,0.02101585],"study_design_scores_gemma":[0.0008891284,0.0005253761,0.008744971,0.0003247285,0.0002071597,0.00003221325,0.0001501192,0.007119629,0.001798713,0.01677232,0.9627427,0.0006929745],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.04015856,0.05017642,0.2661848,0.03457318,0.005965899,0.005856987,0.1413171,0.006134941,0.4496321],"genre_scores_gemma":[0.6807109,0.004334575,0.08785363,0.003673712,0.0298776,0.0001334259,0.1830084,0.0004690031,0.009938806],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6405523,"threshold_uncertainty_score":0.9997,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02665544646872245,"score_gpt":0.2690289833811848,"score_spread":0.2423735369124624,"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."}}