{"id":"W2068944458","doi":"10.1109/usnc-ursi.2014.6955432","title":"Electromagnetic inverse scattering based object imaging and characterization","year":2014,"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 Waterloo","funders":"","keywords":"Microwave imaging; Physics; Inverse scattering problem; Optics; Scattering; Near and far field; Inverse problem; Microwave; Cylinder; Characterization (materials science); Computer science; Geometry; Mathematical analysis; 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":[0.0001188084,0.000124242,0.000122473,0.0001429941,0.00005278196,0.00009161424,0.00005999772,0.00001893349,0.00008508075],"category_scores_gemma":[0.000008859675,0.0001285396,0.00003145676,0.0001271069,0.0000256352,0.00009640776,0.00001356474,0.00007230434,0.00003158936],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002114697,"about_ca_system_score_gemma":0.000003514438,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002098907,"about_ca_topic_score_gemma":0.000006706965,"domain_scores_codex":[0.999422,0.00002261146,0.0001284272,0.0001590663,0.00006374803,0.0002042026],"domain_scores_gemma":[0.9997289,0.00001946293,0.00001480732,0.0001641585,0.00001288178,0.00005980428],"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":[8.716622e-7,0.000002938555,0.005143123,0.00004533863,0.000008906715,8.754642e-7,0.00004272261,0.0006370005,0.9789916,0.000008532455,0.0001923879,0.01492572],"study_design_scores_gemma":[0.0001735442,0.000009369703,0.01141244,0.00002280433,0.00002363269,0.00001265692,0.000008288936,0.9522391,0.03415584,0.00001562055,0.001732644,0.0001940767],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8863147,0.00002938301,0.1103127,0.000302138,0.00007527215,0.00003661714,0.000001157472,0.0004668801,0.002461146],"genre_scores_gemma":[0.9970871,0.00001275933,0.002262316,0.0003990789,0.00005171424,0.000005067262,0.00002127515,0.00002771619,0.0001329981],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9516021,"threshold_uncertainty_score":0.5241691,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003096384003774949,"score_gpt":0.1692947257308637,"score_spread":0.1661983417270888,"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."}}