{"id":"W4210848066","doi":"10.1002/mrm.29170","title":"Improved accuracy and precision with three‐parameter simultaneous myocardial T<sub>1</sub>and T<sub>2</sub>mapping using multiparametric SASHA","year":2022,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Cardiac Imaging and Diagnostics","field":"Medicine","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta Hospital; University of Alberta; University of Calgary","funders":"","keywords":"Coefficient of variation; Nuclear medicine; Accuracy and precision; Reproducibility; Steady-state free precession imaging; Interquartile range; Single shot; Nuclear magnetic resonance; Biomedical engineering; Medicine; Mathematics; Magnetic resonance imaging; Statistics; Physics; Radiology; Optics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00107798,0.0004850427,0.001101156,0.000779068,0.0002787846,0.00005854064,0.000159217,0.0001400931,0.00001937409],"category_scores_gemma":[0.008626173,0.0004068803,0.00009257721,0.001512521,0.0005322031,0.0001140563,0.0003274822,0.000987445,0.000003757419],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002375676,"about_ca_system_score_gemma":0.0001715569,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002952077,"about_ca_topic_score_gemma":0.0000443894,"domain_scores_codex":[0.9963243,0.00020257,0.0007641916,0.000963108,0.001013877,0.0007319783],"domain_scores_gemma":[0.9937195,0.004875978,0.0002362978,0.0006442887,0.0001880749,0.0003359088],"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":[0.001406665,0.0001777368,0.09658172,0.0001918837,0.00004345787,0.001146176,0.001207558,0.001038519,0.1371844,0.000003405134,0.0004108959,0.7606075],"study_design_scores_gemma":[0.02316545,0.005672255,0.6012478,0.002622101,0.0008704122,0.003365163,0.001353571,0.3433858,0.007978371,0.0002991683,0.008742601,0.001297358],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9403625,0.05573863,0.001104416,0.0006955122,0.0004347963,0.001463799,0.00002394969,0.0000814988,0.00009492803],"genre_scores_gemma":[0.9931937,0.002525551,0.002558296,0.001028594,0.0004229897,0.0001404797,0.0000308286,0.00008426079,0.00001532825],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7593102,"threshold_uncertainty_score":0.9998383,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01741285443861323,"score_gpt":0.2622395496439039,"score_spread":0.2448266952052907,"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."}}