{"id":"W2149392970","doi":"10.1002/mrm.24878","title":"Saturation recovery single‐shot acquisition (SASHA) for myocardial <i>T</i><sub>1</sub> mapping","year":2013,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":390,"is_retracted":false,"has_abstract":true,"ca_institutions":"Siemens (Canada); Libin Cardiovascular Institute of Alberta; Montreal Heart Institute; University of Alberta; Université de Montréal; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Fondation pour la Recherche Médicale; Canadian Institutes of Health Research; Alberta Innovates; Alberta Innovates - Health Solutions; Children's Health Research Institute","keywords":"Imaging phantom; Heart rate; Flip angle; Medicine; Nuclear medicine; Heart failure; Steady-state free precession imaging; Reproducibility; Single shot; Biomedical engineering; Saturation (graph theory); Cardiology; Nuclear magnetic resonance; Magnetic resonance imaging; Internal medicine; Blood pressure; Mathematics; Radiology; Physics; Statistics; Optics","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":[0.0002710699,0.0002135887,0.000430624,0.0001940395,0.00008229234,0.00001660955,0.0001017082,0.0001542563,0.0001181087],"category_scores_gemma":[0.0002411855,0.0001863045,0.00008215587,0.0004366872,0.000154712,0.0001646796,0.00002933165,0.0002140995,0.00003009686],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001635944,"about_ca_system_score_gemma":0.00004053891,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004695799,"about_ca_topic_score_gemma":0.00001184978,"domain_scores_codex":[0.9983252,0.00002960033,0.0005431937,0.0004304818,0.0002983505,0.0003731529],"domain_scores_gemma":[0.9989671,0.0001866067,0.0001292087,0.0003979924,0.0002000277,0.0001190284],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001138416,0.00009495902,0.0005847329,0.00006997903,0.000002573687,0.000006205915,0.0001602509,0.00001905264,0.5397626,0.0002892453,0.0189271,0.4399695],"study_design_scores_gemma":[0.01198874,0.007568322,0.3707298,0.00416452,0.0002137828,0.0002433512,0.001097475,0.007400518,0.1177224,0.0419827,0.4356853,0.001202998],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8016081,0.0114656,0.1359762,0.03028654,0.0005790221,0.007774161,0.00002998654,0.0004301979,0.0118502],"genre_scores_gemma":[0.9510864,0.002369178,0.03648809,0.005374817,0.001385762,0.00241366,0.0002560823,0.00006764711,0.0005583655],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4387665,"threshold_uncertainty_score":0.7597279,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02684656668298001,"score_gpt":0.282704881071954,"score_spread":0.255858314388974,"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."}}