{"id":"W1577435501","doi":"10.1002/mrm.24568","title":"Transverse relaxometry with reduced echo train lengths via stimulated echo compensation","year":2013,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Multislice; Echo (communications protocol); Nuclear magnetic resonance; Magnetization transfer; Specific absorption rate; Spin echo; Relaxometry; Grey matter; Physics; White matter; Magnetic resonance imaging; Chemistry; Computer science; Telecommunications; Medicine; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001110277,0.0008347569,0.0004067789,0.0003823528,0.0001893722,0.0004505794,0.0008014247,0.0006372942,0.001530486],"category_scores_gemma":[0.003979547,0.0004779703,0.0003021259,0.0005052639,0.0004519993,0.000953262,0.0005888838,0.0007645116,0.000521384],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002450415,"about_ca_system_score_gemma":0.0004874896,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007628266,"about_ca_topic_score_gemma":0.00229713,"domain_scores_codex":[0.9996399,0.0001342065,0.00002854208,0.00008134899,0.00009039833,0.00002553644],"domain_scores_gemma":[0.9987075,0.0006222291,0.0002449157,0.0002275139,0.0001543192,0.00004353885],"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":[0.0004043851,0.00006846514,0.0009424957,0.0001492269,0.00005510202,0.00008727227,0.0001042548,0.004575938,0.9737191,0.0003788261,0.0001793599,0.01933553],"study_design_scores_gemma":[0.0000667447,0.0007355731,0.004026874,0.00002291904,0.0001029475,0.0005288334,0.00004764418,0.06965902,0.9210077,0.000767735,0.002957223,0.00007666474],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.6562149,0.001011666,0.3393984,0.0002966402,0.00006798351,0.00009838802,0.00018102,0.001775516,0.000955614],"genre_scores_gemma":[0.5334512,0.0008100711,0.4628547,0.0001306394,0.00002686764,0.0001490764,0.0004046913,0.0003515603,0.001821304],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.001530486,"threshold_uncertainty_score":0.005871713,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01649395935965287,"score_gpt":0.2916824664672636,"score_spread":0.2751885071076108,"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."}}