{"id":"W2150175291","doi":"10.1109/tmi.2008.922691","title":"Current Density Impedance Imaging","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Medical Imaging","topic":"Electrical and Bioimpedance Tomography","field":"Engineering","cited_by":58,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Electrical impedance; Medical imaging; Current (fluid); Biomagnetism; Computer science; Physics; Artificial intelligence; Electrical engineering; Engineering; Magnetic field","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":[0.000552465,0.0005850488,0.0006769681,0.001740327,0.0003086331,0.001100348,0.001012794,0.001276709,0.01060751],"category_scores_gemma":[0.002463181,0.0003468009,0.0003037952,0.00122461,0.0005309965,0.001829137,0.0009329981,0.0008737447,0.003468472],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004279689,"about_ca_system_score_gemma":0.0003317549,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005250355,"about_ca_topic_score_gemma":0.0004993813,"domain_scores_codex":[0.9990892,0.0001173558,0.00005443019,0.0002262422,0.0004323321,0.00008045288],"domain_scores_gemma":[0.9990541,0.0002703879,0.00009248325,0.0001466239,0.0003799976,0.00005621999],"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":[0.0004650315,0.0001763982,0.003351106,0.0006211701,0.00003980617,0.0005449968,0.0002996802,0.001547784,0.7224051,0.009986845,0.006943707,0.2536185],"study_design_scores_gemma":[0.0001421121,0.0007282166,0.01220651,0.0001973341,0.0001503713,0.006568309,0.0002957762,0.0474206,0.8234532,0.008590711,0.1001023,0.0001444102],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06161807,0.003064506,0.9035876,0.0007880565,0.0002654166,0.0004511053,0.001279666,0.003889004,0.02505658],"genre_scores_gemma":[0.538669,0.004760419,0.4132918,0.001400481,0.0002804005,0.0007148052,0.00157403,0.0007462052,0.03856289],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01060751,"threshold_uncertainty_score":0.03548568,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008514780299896305,"score_gpt":0.2321600667337787,"score_spread":0.2236452864338824,"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."}}