{"id":"W1963545754","doi":"10.1016/j.zemedi.2007.03.002","title":"STEAM-Sequenz mit Multi-Echo-Auslese für die statische Magnetresonanz-Elastographie","year":2007,"lang":"de","type":"article","venue":"Zeitschrift für Medizinische Physik","topic":"Ultrasound Imaging and Elastography","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Chemistry; Physics; Molecular biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002099225,0.0009429344,0.000874376,0.001565991,0.0002626534,0.0009979735,0.0004199068,0.001091639,0.00567846],"category_scores_gemma":[0.007917196,0.0006630958,0.0009322446,0.0009970821,0.0004483908,0.00166739,0.001160317,0.001180608,0.001658878],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002273514,"about_ca_system_score_gemma":0.0004012637,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006834092,"about_ca_topic_score_gemma":0.000817798,"domain_scores_codex":[0.9993584,0.0003432862,0.00006090717,0.00009981256,0.0001118626,0.00002586748],"domain_scores_gemma":[0.996888,0.002361274,0.000101283,0.0002822712,0.0002864526,0.00008082487],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.004177899,0.0003574131,0.0132407,0.003005052,0.0009813379,0.0006595277,0.0005106306,0.1287543,0.298288,0.01661857,0.004028597,0.529378],"study_design_scores_gemma":[0.0001917064,0.000744215,0.01989815,0.0001586961,0.0005719865,0.001561032,0.0001173382,0.8588579,0.09603882,0.01371414,0.007996316,0.0001497756],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05897292,0.001333557,0.9353395,0.0002863194,0.0001045987,0.0001047468,0.001054872,0.001562194,0.001241248],"genre_scores_gemma":[0.444635,0.001965508,0.5476599,0.000136634,0.0001181728,0.0003630365,0.001732247,0.001063621,0.002325917],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00567846,"threshold_uncertainty_score":0.01899642,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.019234696510761,"score_gpt":0.3162316726221189,"score_spread":0.2969969761113579,"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."}}