{"id":"W2474518491","doi":"10.1002/nbm.3566","title":"Multislice <i>T</i><sub>1</sub>‐prepared 2D single‐shot EPI: analysis of a clinical <i>T</i><sub>1</sub> mapping method unbiased by <i>B</i><sub>0</sub> or <i>B</i><sub>1</sub> inhomogeneity","year":2016,"lang":"en","type":"article","venue":"NMR in Biomedicine","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Foothills Medical Centre; University of Calgary","funders":"Canadian Institutes of Health Research","keywords":"Flip angle; Single shot; Multislice; Echo-planar imaging; Physics; Nuclear magnetic resonance; Nuclear medicine; Computer science; Materials science; Magnetic resonance imaging; Medicine; Optics; Radiology","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":["metaepi_narrow","research_integrity"],"consensus_categories":["metaepi_narrow"],"category_scores_codex":[0.006016238,0.002066882,0.005679627,0.002923974,0.0004622198,0.00007380734,0.001389354,0.001796348,0.00006388334],"category_scores_gemma":[0.003495941,0.001623428,0.00179946,0.01065313,0.001972283,0.0007373093,0.0008048916,0.001800726,0.0001098546],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001048715,"about_ca_system_score_gemma":0.0008006432,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001818946,"about_ca_topic_score_gemma":0.0005366576,"domain_scores_codex":[0.9833153,0.001194109,0.006507643,0.003559729,0.002555722,0.002867512],"domain_scores_gemma":[0.9854391,0.004213239,0.003086619,0.003874347,0.001297183,0.002089578],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001660924,0.00315924,0.005482981,0.0003408609,0.001107402,0.0001774556,0.0004433831,0.00005798779,0.8350635,0.00005649562,0.01159554,0.1408542],"study_design_scores_gemma":[0.0114188,0.001711755,0.008589589,0.002010886,0.003489162,0.0001974736,0.0004634118,0.001314723,0.9550201,0.0002249266,0.01378608,0.001773132],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8206401,0.001470851,0.167992,0.002979616,0.0005868945,0.003510655,0.00135991,0.0009335328,0.0005263683],"genre_scores_gemma":[0.9631053,0.007854563,0.01969936,0.004920148,0.001282968,0.001070403,0.001578488,0.0004350096,0.00005371958],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1482926,"threshold_uncertainty_score":0.9994996,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07439771907292858,"score_gpt":0.3938344737398501,"score_spread":0.3194367546669216,"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."}}