{"id":"W2027022867","doi":"10.1002/mrm.22188","title":"MRI using radiofrequency magnetic field phase gradients","year":2009,"lang":"en","type":"article","venue":"Magnetic Resonance in Medicine","topic":"Advanced MRI Techniques and Applications","field":"Medicine","cited_by":61,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Institute for Biodiagnostics","funders":"","keywords":"Nuclear magnetic resonance; Phase (matter); Magnetic field; Field (mathematics); Magnetic resonance imaging; Physics; Medicine; Radiology; Mathematics","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":[0.0004220782,0.0004352545,0.0003041786,0.0002917298,0.0001625881,0.0006373006,0.0004260452,0.0005920542,0.0009024983],"category_scores_gemma":[0.0007150982,0.0002950471,0.0001928745,0.0002639606,0.0007716924,0.001150504,0.0004714096,0.0005141451,0.0008264052],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000140327,"about_ca_system_score_gemma":0.0002209893,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001621065,"about_ca_topic_score_gemma":0.0002647901,"domain_scores_codex":[0.9998502,0.00004052299,0.000008818929,0.00004559269,0.00004281575,0.00001208284],"domain_scores_gemma":[0.999742,0.0001121324,0.00005110771,0.00004079249,0.00003513429,0.00001881385],"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":[0.0001891745,0.00003512654,0.0003205562,0.0004261154,0.00004002066,0.0002373946,0.00008447758,0.0007907894,0.8934703,0.008558195,0.001171449,0.09467641],"study_design_scores_gemma":[0.000105644,0.001030924,0.002351554,0.0001606418,0.0001029031,0.005257864,0.00005455979,0.008672958,0.9098666,0.01021409,0.06207331,0.000108845],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08649493,0.01884907,0.8752916,0.001208133,0.0004833005,0.0001845784,0.0001557263,0.001505734,0.01582681],"genre_scores_gemma":[0.3898467,0.01466148,0.5854585,0.001532797,0.0004650102,0.0002237375,0.0001733907,0.0002279795,0.007410408],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0009024983,"threshold_uncertainty_score":0.003019154,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02866404574634335,"score_gpt":0.3700970634214982,"score_spread":0.3414330176751549,"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."}}