{"id":"W2625188121","doi":"10.1161/circimaging.116.003951","title":"Recent Advances in Cardiovascular Magnetic Resonance","year":2017,"lang":"en","type":"review","venue":"Circulation Cardiovascular Imaging","topic":"Cardiac Imaging and Diagnostics","field":"Medicine","cited_by":186,"is_retracted":false,"has_abstract":true,"ca_institutions":"NOSM University","funders":"National Institute of Biomedical Imaging and Bioengineering; National Heart, Lung, and Blood Institute","keywords":"Medicine; Magnetic resonance imaging; Coronary artery disease; Cardiology; Heart failure; Myocardial fibrosis; Cardiac magnetic resonance imaging; Internal medicine; Radiology; Heart disease","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":[0.0009886444,0.000838435,0.0009616265,0.003162308,0.0003397718,0.001325996,0.0008391984,0.001239178,0.007956829],"category_scores_gemma":[0.001907758,0.0002863084,0.0006596266,0.002310623,0.0005263647,0.001716823,0.0007948236,0.001992405,0.003853741],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006297249,"about_ca_system_score_gemma":0.001543746,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0011341,"about_ca_topic_score_gemma":0.00155542,"domain_scores_codex":[0.99968,0.00004846659,0.00005371761,0.00006228274,0.000123176,0.00003221448],"domain_scores_gemma":[0.9986979,0.000668384,0.000126545,0.00003963176,0.0003722053,0.00009530712],"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":[0.00006092111,0.00006369797,0.0004373584,0.01378185,0.00007722059,0.0003693712,0.00009382355,0.0002417397,0.001600118,0.003764451,0.03889427,0.9406152],"study_design_scores_gemma":[0.000009558215,0.00006212515,0.000959085,0.002857102,0.0001113384,0.002671866,0.00006386766,0.0001055997,0.0005108059,0.002319562,0.9903007,0.00002843909],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001658736,0.9961835,0.0002800978,0.0006443129,0.0005274779,0.000005219801,0.00002414205,0.00001909805,0.002150359],"genre_scores_gemma":[0.001147421,0.9958717,0.0004950189,0.0004627367,0.001042839,0.000007229393,0.00005440594,0.000004152268,0.0009144612],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.007956829,"threshold_uncertainty_score":0.02661824,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04461964683870135,"score_gpt":0.3298435456042464,"score_spread":0.2852238987655451,"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."}}