{"id":"W4220848269","doi":"10.1088/2057-1976/ac5bf1","title":"Improvement of performance and sensitivity of 2D and 3D image reconstruction in EIT using EFG forward model","year":2022,"lang":"en","type":"article","venue":"Biomedical Physics & Engineering Express","topic":"Electrical and Bioimpedance Tomography","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Jacobian matrix and determinant; Electrical impedance tomography; Computation; Finite element method; Algorithm; Iterative reconstruction; Inverse; Matrix (chemical analysis); Computer science; Sensitivity (control systems); Galerkin method; Tomography; Mathematics; Artificial intelligence; Physics; Optics; Electronic engineering; Materials science; Engineering; Geometry; Applied 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":[0.0007762261,0.0006428135,0.0004653255,0.0004546309,0.0002400839,0.0006990589,0.0006981379,0.001254686,0.001320312],"category_scores_gemma":[0.00254638,0.0002775627,0.0005417598,0.0003904373,0.0004204131,0.00106274,0.0008831237,0.0007258328,0.000526387],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003157658,"about_ca_system_score_gemma":0.0005354316,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002491398,"about_ca_topic_score_gemma":0.001774948,"domain_scores_codex":[0.9996443,0.00008145251,0.00001705305,0.00005944526,0.0001734392,0.00002442564],"domain_scores_gemma":[0.9994337,0.0003049223,0.00003763212,0.00008463199,0.0001216441,0.00001740725],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000322339,0.00008962416,0.003598886,0.0003796904,0.00006015601,0.0004881262,0.0004086027,0.595779,0.09921908,0.01471305,0.001617669,0.2833238],"study_design_scores_gemma":[0.000004645627,0.00001713415,0.0002229779,0.000007508191,0.000005927161,0.0001457284,0.00001494648,0.9844935,0.01311886,0.001029113,0.0009282283,0.00001133409],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01446644,0.0001919576,0.9836828,0.0001218597,0.00001917957,0.00001799601,0.00003008471,0.0004555541,0.001014113],"genre_scores_gemma":[0.356583,0.0005594455,0.6395595,0.0001640287,0.00002368029,0.00009144069,0.0002108264,0.0002261063,0.00258204],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002491398,"threshold_uncertainty_score":0.004953802,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005445889534003213,"score_gpt":0.1837080084121444,"score_spread":0.1782621188781412,"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."}}