{"id":"W4388286349","doi":"10.1109/lawp.2023.3328003","title":"The Time-Reversal Method for Source Reconstructions Within a Metallic Cavity: An Experimental Validation","year":2023,"lang":"en","type":"article","venue":"IEEE Antennas and Wireless Propagation Letters","topic":"Geophysical Methods and Applications","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Fujian Provincial Department of Science and Technology; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Time domain; Interference (communication); Wideband; Electromagnetic interference; Computer science; Frequency domain; Network analyzer (electrical); Acoustics; Electronic engineering; Physics; Algorithm; Engineering; Telecommunications","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":[0.0003700164,0.0001273423,0.000133189,0.00005707888,0.0004180789,0.0001182237,0.00009055861,0.00004287016,0.000003429688],"category_scores_gemma":[0.00001287615,0.00010161,0.00005669181,0.0002503307,0.00007682756,0.0002034314,0.00001110857,0.00009641726,0.00001980791],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000216692,"about_ca_system_score_gemma":0.000007693335,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002005999,"about_ca_topic_score_gemma":0.00000351734,"domain_scores_codex":[0.9992163,0.00007607645,0.0002048971,0.0002087995,0.0001024741,0.0001914905],"domain_scores_gemma":[0.9995021,0.000173283,0.00005531593,0.000166373,0.00003766894,0.00006528128],"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":[0.000006879951,0.00001090197,0.000007268088,0.00001370435,0.00002867833,2.483269e-7,0.0003290896,0.001847647,0.9750428,0.001167829,0.0004193805,0.02112558],"study_design_scores_gemma":[0.0003847788,0.00005944886,0.0002716507,0.00001954156,0.00005156649,0.00001249,0.0007425463,0.6882901,0.3065197,0.001393644,0.001965909,0.0002887182],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7879516,0.00001077735,0.2097704,0.001359445,0.0002218281,0.0003927779,0.00001378838,0.0002674568,0.00001184332],"genre_scores_gemma":[0.9763757,0.00002049853,0.02221844,0.0002289776,0.000246294,0.0005947894,0.00005629859,0.00004706793,0.0002119423],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6864424,"threshold_uncertainty_score":0.4143535,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01830478494171998,"score_gpt":0.2768661160785702,"score_spread":0.2585613311368502,"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."}}