{"id":"W4384637631","doi":"10.2528/pier23032403","title":"Remote Material Characterization with Complex Baseband FMCW Radar Sensors","year":2023,"lang":"en","type":"article","venue":"Electromagnetic waves","topic":"Sensor Technology and Measurement Systems","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"CMC Microsystems (Canada); University of Waterloo","funders":"","keywords":"Baseband; Remote sensing; Continuous-wave radar; Radar; Characterization (materials science); Computer science; Geology; Materials science; Radar imaging; Telecommunications; Bandwidth (computing); Nanotechnology","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":[0.0004872578,0.000458338,0.0003437344,0.0007153368,0.0001616429,0.000528286,0.0005856923,0.0005637167,0.001034194],"category_scores_gemma":[0.0009343107,0.000185829,0.0002455143,0.0002945676,0.0004697749,0.001006034,0.0003913715,0.0004226493,0.0005682384],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002318338,"about_ca_system_score_gemma":0.0001095697,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001309459,"about_ca_topic_score_gemma":0.0002047036,"domain_scores_codex":[0.9994913,0.00007953636,0.00001682307,0.00009874039,0.0002819994,0.0000314909],"domain_scores_gemma":[0.9995342,0.0001783198,0.00009497556,0.00008521409,0.00009470766,0.00001250812],"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":[0.00006810929,0.00004320229,0.0006626626,0.0001389842,0.00001273586,0.00006742052,0.00008915913,0.003525518,0.9536106,0.001406989,0.0001762294,0.04019845],"study_design_scores_gemma":[0.00001578759,0.0002772293,0.002392784,0.00002380066,0.0000222339,0.0003626564,0.0001007094,0.05678741,0.9352471,0.0009066068,0.003834717,0.00002898558],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2338907,0.0008088699,0.7598833,0.0001489414,0.00009012053,0.0001045836,0.0001269788,0.0008678971,0.004078628],"genre_scores_gemma":[0.687871,0.0006033061,0.3089296,0.0001333686,0.0000525658,0.00008558993,0.0001676796,0.00009746538,0.002059471],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001034194,"threshold_uncertainty_score":0.003459752,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0169673788013231,"score_gpt":0.2142825915653106,"score_spread":0.1973152127639875,"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."}}