{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002023927,0.0002272849,0.0004667914,0.0002212688,0.00006562285,0.00000617848,0.0001808205,0.00011633,0.0006689569],"category_scores_gemma":[0.0001844886,0.0001902293,0.00005404743,0.0006728652,0.0001567778,0.00006292624,0.00001869505,0.0003437665,0.000011471],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001048671,"about_ca_system_score_gemma":0.00004898187,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001144432,"about_ca_topic_score_gemma":0.000004846653,"domain_scores_codex":[0.9982464,0.00002681203,0.0005375878,0.0004273621,0.000331982,0.0004298675],"domain_scores_gemma":[0.999005,0.00007366626,0.00008166457,0.0005813698,0.00007109889,0.0001871821],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000185004,0.0004684903,0.002470948,0.00002975973,9.735503e-7,0.0002695513,0.0002365521,0.00001349088,0.02504844,0.001803657,0.005046796,0.9644263],"study_design_scores_gemma":[0.03238523,0.04043306,0.07347878,0.004586099,0.0003572361,0.001525636,0.0005431069,0.02825857,0.00782601,0.05042443,0.7587909,0.001390929],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.679869,0.1556709,0.06519859,0.05145865,0.0004515478,0.004425647,0.00001633987,0.0005770737,0.04233229],"genre_scores_gemma":[0.8473055,0.01016196,0.1284651,0.009715273,0.0007377182,0.0001409913,0.00003432107,0.00005595869,0.003383181],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9630354,"threshold_uncertainty_score":0.7757328,"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."}}