{"id":"W3217105868","doi":"10.3389/fninf.2021.622951","title":"Magnetic Resonance Imaging Sequence Identification Using a Metadata Learning Approach","year":2021,"lang":"en","type":"article","venue":"Frontiers in Neuroinformatics","topic":"Biomedical Text Mining and Ontologies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Heart and Stroke Foundation; Centre for Addiction and Mental Health; Queen's University; St. Joseph’s Healthcare Hamilton; Western University; University of Toronto; University of British Columbia; Hospital for Sick Children; University of Calgary; University Health Network; Health Sciences Centre; St. Michael's Hospital; Sunnybrook Health Science Centre; McMaster University; Robarts Clinical Trials; Indoc Research; Holland Bloorview Kids Rehabilitation Hospital; Baycrest Hospital","funders":"Faculty of Health Sciences, Queen's University; Natural Sciences and Engineering Research Council of Canada; Temerty Family Foundation; H. Lundbeck A/S; Servier; University of British Columbia; London Health Sciences Foundation; Government of Ontario; University of Ottawa; Hospital for Sick Children; Pfizer; Ontario Brain Institute; University of Calgary; Queen's University; Canadian Institutes of Health Research; Centre for Addiction and Mental Health Foundation; McMaster University; Bristol-Myers Squibb","keywords":"Computer science; Metadata; Identification (biology); Artificial intelligence; Magnetic resonance imaging; Sequence (biology); Machine learning; A priori and a posteriori; Software; Information retrieval; Data mining; World Wide Web; Medicine; Radiology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003206718,0.0007964836,0.0008089226,0.008701532,0.00132409,0.001966667,0.001947175,0.001549528,0.001455635],"category_scores_gemma":[0.0094808,0.0003536728,0.001742984,0.004839281,0.0008780675,0.004054731,0.002047394,0.001514493,0.001958078],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001521629,"about_ca_system_score_gemma":0.003971074,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007133438,"about_ca_topic_score_gemma":0.01135528,"domain_scores_codex":[0.9970822,0.0005207295,0.0004883357,0.0009395101,0.0008013929,0.0001679428],"domain_scores_gemma":[0.9944113,0.001890388,0.0008751407,0.0009873507,0.001609262,0.000226648],"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":[0.000381272,0.0008258091,0.02699317,0.0004695909,0.0001599392,0.0006552623,0.0005369029,0.03136804,0.01875754,0.01664331,0.01477166,0.8884376],"study_design_scores_gemma":[0.00007232859,0.000322595,0.009109878,0.0002362299,0.0002200081,0.001701203,0.00104705,0.8534048,0.02898403,0.0674068,0.03734001,0.000155142],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02092527,0.0005549612,0.9682755,0.0007253133,0.0001200022,0.0004250669,0.002531405,0.00425053,0.002192011],"genre_scores_gemma":[0.1407603,0.0005100629,0.8435732,0.0003563327,0.0001794428,0.000435141,0.01119814,0.0001840959,0.002803314],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008701532,"threshold_uncertainty_score":0.01695895,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02552399238093964,"score_gpt":0.2662290727434171,"score_spread":0.2407050803624774,"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."}}