{"id":"W2530547764","doi":"10.1161/circimaging.116.005593","title":"Magnetic Resonance Diffusion Tensor Imaging Provides New Insights Into the Microstructural Alterations in Dilated Cardiomyopathy","year":2016,"lang":"en","type":"letter","venue":"Circulation Cardiovascular Imaging","topic":"Cardiovascular Function and Risk Factors","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Heart, Lung, and Blood Institute; Engineering and Physical Sciences Research Council","keywords":"Medicine; Magnetic resonance imaging; Dilated cardiomyopathy; Diffusion MRI; Cardiomyopathy; Cardiac magnetic resonance; Heart failure; Nuclear magnetic resonance; Cardiology; Radiology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001526862,0.0007646249,0.0007508658,0.0021499,0.0003369403,0.001580228,0.0002305958,0.0008953132,0.007266471],"category_scores_gemma":[0.002320799,0.0003597311,0.0004325942,0.0009045519,0.000959693,0.001213081,0.0005444874,0.001614979,0.001655697],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000479519,"about_ca_system_score_gemma":0.0007282624,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008653253,"about_ca_topic_score_gemma":0.001965746,"domain_scores_codex":[0.9995363,0.0001205813,0.00005241469,0.00007060146,0.0001636915,0.00005643938],"domain_scores_gemma":[0.9988949,0.0003535268,0.0002504013,0.0001062155,0.0002796905,0.0001153098],"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":[0.001394604,0.0004177302,0.1070284,0.002082422,0.0008702302,0.01118734,0.0008586193,0.002144202,0.08996803,0.01321728,0.1253149,0.6455163],"study_design_scores_gemma":[0.0005526834,0.0008263169,0.6361739,0.003108373,0.001082038,0.04001405,0.001499249,0.01587216,0.03832657,0.04853845,0.2136493,0.0003569457],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4095498,0.3343615,0.08282874,0.06432593,0.006205044,0.0004233909,0.003012113,0.002196965,0.09709659],"genre_scores_gemma":[0.7441528,0.1772216,0.03262241,0.004411083,0.01424671,0.0001949887,0.001783379,0.0005185849,0.02484833],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007266471,"threshold_uncertainty_score":0.02430874,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008734406634236207,"score_gpt":0.2174446557790957,"score_spread":0.2087102491448595,"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."}}