{"id":"W2117828918","doi":"10.1186/1532-429x-12-69","title":"Shortened Modified Look-Locker Inversion recovery (ShMOLLI) for clinical myocardial T1-mapping at 1.5 and 3 T within a 9 heartbeat breathhold","year":2010,"lang":"en","type":"article","venue":"Journal of Cardiovascular Magnetic Resonance","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":664,"is_retracted":false,"has_abstract":true,"ca_institutions":"Libin Cardiovascular Institute of Alberta","funders":"Clarendon Fund; NIHR Oxford Biomedical Research Centre; Fondation pour la Recherche Médicale; University of Oxford; Alberta Heritage Foundation for Medical Research; National Institute for Health and Care Research","keywords":"Medicine; Angiology; Myocardial infarction; Nuclear medicine; Imaging phantom; Gold standard (test); Heartbeat; Scanner; Cardiology; Internal medicine; Biomedical engineering; Artificial intelligence; Computer science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001530122,0.0002068753,0.0009010012,0.0001234872,0.0001379913,0.0000272257,0.0001319992,0.000245346,0.00001169662],"category_scores_gemma":[0.0002939871,0.0001716697,0.001294679,0.0001682014,0.0001754423,0.0001256321,0.00006871133,0.0005668871,0.00000240717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005533523,"about_ca_system_score_gemma":0.0001286409,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008937219,"about_ca_topic_score_gemma":0.000003074709,"domain_scores_codex":[0.9980059,0.00007053994,0.0008017015,0.000363539,0.0004951257,0.0002632366],"domain_scores_gemma":[0.9983311,0.0001607388,0.0002359716,0.0006115159,0.0003830745,0.0002775613],"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":[0.001991555,0.0002163685,0.005550008,0.0001327255,0.0005856093,0.0002349338,0.000135436,0.0003617881,0.01154156,0.0003364375,0.008173604,0.97074],"study_design_scores_gemma":[0.005342476,0.001402369,0.0296519,0.0002701796,0.001009107,0.002580263,0.00004782224,0.002098826,0.002467922,0.001400477,0.9534167,0.0003119351],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8773791,0.08007225,0.03896651,0.0009751808,0.0005924608,0.001256512,0.0000196442,0.00005056694,0.0006878038],"genre_scores_gemma":[0.6244594,0.08344766,0.2859066,0.001279172,0.002903413,0.0001508405,0.00001529198,0.0001393836,0.001698193],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.970428,"threshold_uncertainty_score":0.7000489,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0334484957467173,"score_gpt":0.3056658378102749,"score_spread":0.2722173420635576,"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."}}