{"id":"W2136033789","doi":"10.1109/tmi.2010.2078513","title":"Radio-Frequency Current Density Imaging Based on a 180$^\\circ$ Sample Rotation With Feasibility Study of Full Current Density Vector Reconstruction","year":2010,"lang":"en","type":"article","venue":"IEEE Transactions on Medical Imaging","topic":"Electrical and Bioimpedance Tomography","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Current (fluid); Current density; Sample (material); Rotation (mathematics); Iterative reconstruction; Radio frequency; Nuclear magnetic resonance; Physics; Computer science; Artificial intelligence; Telecommunications","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":[0.001303424,0.0004678935,0.0005540861,0.0002470757,0.0001777136,0.0005714413,0.0006390918,0.0004772097,0.001062973],"category_scores_gemma":[0.003158304,0.0003838648,0.0002419641,0.000318966,0.0008949063,0.001097361,0.0004736015,0.0003849798,0.0002675683],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002332272,"about_ca_system_score_gemma":0.000507623,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000492578,"about_ca_topic_score_gemma":0.0003023274,"domain_scores_codex":[0.999569,0.0001129561,0.00001737383,0.00006945158,0.0001950889,0.00003616244],"domain_scores_gemma":[0.9988523,0.0005245998,0.0001760134,0.0002239253,0.0001724924,0.00005066601],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001481427,0.0002792302,0.004360245,0.0004514334,0.00007124685,0.0007324965,0.0003632465,0.05190651,0.7709892,0.04004747,0.001224226,0.1280932],"study_design_scores_gemma":[0.0001040108,0.0006758806,0.001778836,0.00003158809,0.00003955911,0.001044614,0.00004634244,0.4976231,0.4909612,0.002385429,0.005243202,0.0000663745],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1767571,0.0004221503,0.8185281,0.0003369141,0.00004239208,0.0001629092,0.00006041447,0.0004152346,0.003274768],"genre_scores_gemma":[0.4764521,0.0002821259,0.5220105,0.0000511341,0.00002074249,0.000113254,0.00008978457,0.00005233398,0.0009280663],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001303424,"threshold_uncertainty_score":0.006893218,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01041441642303555,"score_gpt":0.2489107871742419,"score_spread":0.2384963707512064,"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."}}