{"id":"W2588533727","doi":"10.1109/antem.2000.7851662","title":"Using the unrelated illumination method in the reconstruction of three dimensional dielectric bodies","year":2000,"lang":"en","type":"article","venue":"","topic":"Microwave Imaging and Scattering Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Microwave imaging; Inverse scattering problem; Diffraction tomography; Inverse problem; Regularization (linguistics); A priori and a posteriori; Iterative method; Iterative reconstruction; Scattering; Algebraic equation; Diffraction; Applied mathematics; Method of moments (probability theory); Mathematical analysis; Computer science; Algorithm; Mathematics; Optics; Physics; Microwave; Nonlinear system; Artificial intelligence; Quantum mechanics","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":[0.0006547316,0.000460865,0.0005740495,0.00059765,0.00025475,0.0006706819,0.0005969935,0.00098341,0.001375605],"category_scores_gemma":[0.001105079,0.0002660899,0.0005196037,0.000770845,0.0007917642,0.0006835089,0.0007587745,0.0007598313,0.0007857985],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002674958,"about_ca_system_score_gemma":0.0004605914,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008859188,"about_ca_topic_score_gemma":0.0009930941,"domain_scores_codex":[0.9997341,0.00009573349,0.000008944219,0.00003943425,0.0001078252,0.00001395783],"domain_scores_gemma":[0.9997813,0.0001305628,0.0000185658,0.00002840731,0.00002967234,0.00001143911],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002409841,0.00009100313,0.001000906,0.0006678527,0.00009303761,0.0007586351,0.0004115439,0.2415141,0.08097759,0.1573736,0.005330843,0.5115399],"study_design_scores_gemma":[0.00002214478,0.00006203767,0.0003811062,0.00004268226,0.00002630064,0.0006548621,0.00003162313,0.9458517,0.01853518,0.01834176,0.01600802,0.00004261316],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001740527,0.000339394,0.9969037,0.0000518906,0.0000222736,0.00001158366,0.00001515276,0.00008107287,0.0008343067],"genre_scores_gemma":[0.04371242,0.001366129,0.9515468,0.0001042675,0.00005547147,0.00005773293,0.00009640825,0.00007600476,0.002984716],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001375605,"threshold_uncertainty_score":0.004601896,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0193207890840099,"score_gpt":0.2501963264097959,"score_spread":0.230875537325786,"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."}}