{"id":"W3097918907","doi":"10.1148/radiol.2020200723","title":"Thin-Slice Pituitary MRI with Deep Learning–based Reconstruction: Diagnostic Performance in a Postoperative Setting","year":2020,"lang":"en","type":"article","venue":"Radiology","topic":"Pituitary Gland Disorders and Treatments","field":"Medicine","cited_by":130,"is_retracted":false,"has_abstract":true,"ca_institutions":"CARE Canada; University of Calgary","funders":"","keywords":"Medicine; Pituitary adenoma; Nuclear medicine; Neuroradiology; Radiology; Magnetic resonance imaging; Receiver operating characteristic; Adenoma; Pathology; Neurology; Internal medicine","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":[0.003452625,0.00049244,0.0004191811,0.0007816933,0.0001838186,0.000705131,0.0005008965,0.0004358418,0.0004290592],"category_scores_gemma":[0.01212358,0.0003228416,0.0003028983,0.0004044967,0.0005084947,0.0005919571,0.0006270046,0.0004084419,0.0001661018],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002877706,"about_ca_system_score_gemma":0.0003976879,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001362528,"about_ca_topic_score_gemma":0.001993541,"domain_scores_codex":[0.9990853,0.0004211955,0.0001285364,0.0001503744,0.0001539838,0.00006060705],"domain_scores_gemma":[0.9945385,0.002791641,0.001098296,0.0005386687,0.0007118679,0.0003210072],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00809308,0.0004978633,0.8017426,0.0003433241,0.0004657057,0.002025791,0.0003890831,0.01625577,0.04140859,0.0002931186,0.000625695,0.1278594],"study_design_scores_gemma":[0.0003909781,0.005672778,0.5068851,0.0001497875,0.0006065745,0.01600863,0.0007085858,0.4201813,0.04668651,0.001441629,0.001087057,0.0001811514],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9913919,0.0005354166,0.007480435,0.00007876057,0.00000861375,0.00003490922,0.00009469322,0.00006991516,0.0003053107],"genre_scores_gemma":[0.9883953,0.0002278028,0.01112614,0.00003124572,0.00001163325,0.00001808756,0.0001360091,0.00001265849,0.00004098017],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003452625,"threshold_uncertainty_score":0.01825947,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007820475400967346,"score_gpt":0.2187758229561885,"score_spread":0.2109553475552212,"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."}}