{"id":"W2235070546","doi":"10.1097/rli.0000000000000170","title":"Magnetic Resonance Imaging and Computed Tomography of the Brain—50 Years of Innovation, With a Focus on the Future","year":2015,"lang":"en","type":"review","venue":"Investigative Radiology","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Magnetic resonance imaging; Medical physics; Medical imaging; Focus (optics); Medicine; Workflow; Neuroimaging; Computer science; Preclinical imaging; Radiology; Physics","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":[0.0002309376,0.0001787697,0.0007647995,0.0001442513,0.00003766789,0.000002193162,0.0001846049,0.0001103941,0.000002881979],"category_scores_gemma":[0.0001341783,0.00008953457,0.00006415009,0.001282073,0.001843258,0.00001353254,0.00005447928,0.000379235,3.576409e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002665374,"about_ca_system_score_gemma":0.0002586997,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007304899,"about_ca_topic_score_gemma":0.000002376729,"domain_scores_codex":[0.9989684,0.0001753453,0.0003933403,0.0002331556,0.0001152068,0.0001145326],"domain_scores_gemma":[0.9984334,0.0003107777,0.0005128131,0.0004397419,0.0002674252,0.0000359125],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001631134,0.00002874513,0.0003387357,0.0006087371,0.00003324763,0.000003026473,0.0001942886,9.314175e-7,0.00004740418,0.1290033,0.008101585,0.8616237],"study_design_scores_gemma":[0.0002348221,0.0003008634,0.002455211,0.003753114,0.0001528593,0.0001663061,0.00004746281,0.000007418848,0.00005201724,0.01843606,0.9742901,0.0001037491],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0003232039,0.9932826,0.0004202406,0.004327106,0.00002572262,0.001269718,0.00006231907,0.00002263511,0.000266499],"genre_scores_gemma":[0.001328591,0.9734825,0.02230686,0.001934558,0.0002704622,0.0004429639,0.00006855262,0.00006876928,0.00009671946],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9661885,"threshold_uncertainty_score":0.6791559,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03303237040539733,"score_gpt":0.3156103933392535,"score_spread":0.2825780229338562,"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."}}