{"id":"W2335887429","doi":"10.1109/lawp.2016.2554059","title":"Using the Source Reconstruction Method to Model Incident Fields in Microwave Tomography","year":2016,"lang":"en","type":"article","venue":"IEEE Antennas and Wireless Propagation Letters","topic":"Microwave Imaging and Scattering Analysis","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; University of Manitoba","keywords":"Microwave imaging; Iterative reconstruction; Tomography; Inversion (geology); Microwave; Optics; Computer science; Calibration; Time domain; Frequency domain; Physics; Computer vision; Telecommunications; Geology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008334079,0.0007206522,0.0003687146,0.0005605317,0.0002029804,0.000610059,0.0007773364,0.001157659,0.001208281],"category_scores_gemma":[0.002246958,0.000426481,0.0005207733,0.0006030518,0.0006294373,0.001289696,0.0006614616,0.001158286,0.0007945479],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002823542,"about_ca_system_score_gemma":0.0005016111,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009483999,"about_ca_topic_score_gemma":0.0008154087,"domain_scores_codex":[0.9997184,0.00008850577,0.00001224011,0.00003430977,0.0001311906,0.00001535631],"domain_scores_gemma":[0.9996265,0.0001882806,0.00003492539,0.00005902539,0.00007995386,0.00001129936],"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":[0.0001324587,0.0000899336,0.001253003,0.000206976,0.00005475069,0.0004594242,0.000188472,0.7295009,0.06710231,0.0858629,0.001642643,0.1135061],"study_design_scores_gemma":[0.000007476032,0.00002046097,0.0001039092,0.00001110971,0.000005247059,0.0001686546,0.00001162629,0.9763414,0.0131018,0.008094507,0.002119401,0.00001433674],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001487524,0.00003687547,0.997847,0.00002913436,0.000008849149,0.00001211728,0.00001429856,0.0001105854,0.0004537939],"genre_scores_gemma":[0.1192631,0.0005927269,0.8766594,0.0001020527,0.00003928432,0.0001269929,0.0002001397,0.0002286328,0.00278779],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001208281,"threshold_uncertainty_score":0.004407525,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01610144898952201,"score_gpt":0.2402963602053426,"score_spread":0.2241949112158206,"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."}}