{"id":"W2461679810","doi":"10.1002/jmri.25149","title":"Diagnostic quality assessment of compressed sensing accelerated magnetic resonance neuroimaging","year":2016,"lang":"en","type":"article","venue":"Journal of Magnetic Resonance Imaging","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hamilton Health Sciences; Robarts Clinical Trials; McMaster University; Juravinski Hospital; Juravinski Cancer Centre; Western University","funders":"","keywords":"Fluid-attenuated inversion recovery; Nuclear medicine; Magnetic resonance imaging; Acceleration; Wilcoxon signed-rank test; Compressed sensing; Medicine; Nuclear magnetic resonance; Neuroimaging; Image quality; Radiology; Physics; Computer science; Artificial intelligence; Internal medicine; Image (mathematics)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004091204,0.0005578123,0.0003043561,0.001198528,0.0001657855,0.0006930421,0.0004158353,0.0007756944,0.0009025954],"category_scores_gemma":[0.02436767,0.000199325,0.0002121184,0.0002711461,0.0007707268,0.0005634849,0.0006002917,0.0003065334,0.0001535205],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002275724,"about_ca_system_score_gemma":0.0001889639,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005364937,"about_ca_topic_score_gemma":0.0004988518,"domain_scores_codex":[0.9987458,0.0005249265,0.0001242013,0.0001375843,0.0004121783,0.00005534629],"domain_scores_gemma":[0.9903515,0.004249726,0.001900585,0.0007438658,0.002419853,0.0003344006],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.01354232,0.0004043838,0.2623129,0.0009662554,0.0006688439,0.001571676,0.001373644,0.01709609,0.349919,0.0008085135,0.0009483271,0.3503881],"study_design_scores_gemma":[0.0005918519,0.009709333,0.5212653,0.0002406486,0.0008655658,0.01383989,0.0005896598,0.1874569,0.2605757,0.002622035,0.002036622,0.000206441],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9748206,0.0009211476,0.0230711,0.00017688,0.00002162526,0.00007302029,0.00009998028,0.0001400539,0.0006756877],"genre_scores_gemma":[0.9873109,0.0001526799,0.01227614,0.00002705337,0.00002591974,0.00001255295,0.0001017745,0.00002020001,0.0000728107],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004091204,"threshold_uncertainty_score":0.02163661,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04157795495740788,"score_gpt":0.3693596374650882,"score_spread":0.3277816825076803,"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."}}