{"id":"W2029981818","doi":"10.1109/antem.2014.6887661","title":"Use of synthesized fields in microwave tomography inversion","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 Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Inversion (geology); Tomography; Scattering; Microwave imaging; Omnidirectional antenna; Microwave; Optics; Iterative reconstruction; Inverse scattering problem; Computer science; Inverse transform sampling; Physics; Geology; Computer vision; Telecommunications; Surface wave; Seismology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001028961,0.00007325056,0.000151157,0.0002175529,0.000008296563,0.00001371862,0.00006779474,0.00004414812,0.00005028883],"category_scores_gemma":[0.00002683381,0.00006892635,0.0000756826,0.0002048063,0.00001801226,0.00005628841,0.00001381466,0.00007070523,0.0000105468],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008640246,"about_ca_system_score_gemma":0.00000156363,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00019979,"about_ca_topic_score_gemma":0.00011786,"domain_scores_codex":[0.9995686,0.00002385603,0.0001544941,0.00008681032,0.00005205083,0.0001141854],"domain_scores_gemma":[0.9996833,0.00008602412,0.00001350695,0.0001790158,0.00001107598,0.00002707309],"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":[0.00001595907,0.00004947988,0.04982697,0.0002216835,0.0001233173,0.000004241567,0.0005782177,0.02472421,0.8688776,0.0001899745,0.01287394,0.04251442],"study_design_scores_gemma":[0.000352416,0.00002161467,0.007469423,0.0001282878,0.00003878816,0.000002685063,0.00005516899,0.3716155,0.6150952,0.0002706183,0.004632224,0.0003180738],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9650294,0.00003646657,0.03155021,0.00008069296,0.00005259278,0.00002503772,8.901608e-7,0.00009257903,0.003132172],"genre_scores_gemma":[0.9958159,0.00002205175,0.003957045,0.00007205064,0.000009187003,0.000001186235,0.000001805191,0.000009196575,0.000111624],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3468913,"threshold_uncertainty_score":0.2810735,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01111924142835726,"score_gpt":0.1825112946189159,"score_spread":0.1713920531905587,"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."}}