{"id":"W2990755211","doi":"10.3390/electronics8121447","title":"MIMO Radar Using a Vector Network Analyzer","year":2019,"lang":"en","type":"article","venue":"Electronics","topic":"Radar Systems and Signal Processing","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Military College of Canada","funders":"","keywords":"MIMO; Electronic engineering; Radar; Computer science; Bandwidth (computing); Network analyzer (electrical); Spectrum analyzer; Signal processing; Radar engineering details; Continuous-wave radar; Engineering; Radar imaging; Telecommunications; Beamforming","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":[0.0004936478,0.0007211242,0.0003498332,0.0004792824,0.0002032833,0.0006539178,0.0005476956,0.000330716,0.005465678],"category_scores_gemma":[0.000796421,0.0002591592,0.0001629578,0.00032105,0.0001328832,0.0008887635,0.0004239316,0.0004959324,0.001648891],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003543771,"about_ca_system_score_gemma":0.0004400348,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007464777,"about_ca_topic_score_gemma":0.001004222,"domain_scores_codex":[0.999401,0.0001380709,0.0000344694,0.0001456943,0.0002518582,0.00002900376],"domain_scores_gemma":[0.9995796,0.0001345638,0.00004471854,0.0000552393,0.0001648051,0.00002112751],"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":[0.0006961297,0.0003099469,0.00427183,0.0004712988,0.0001467524,0.0002877368,0.0002411522,0.05303741,0.5339424,0.01729573,0.008985336,0.3803142],"study_design_scores_gemma":[0.0001597616,0.001080069,0.003642408,0.00004594076,0.0001017019,0.0006847068,0.00005463013,0.7191675,0.231629,0.002313572,0.04104669,0.0000741675],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03476765,0.0001886904,0.9476758,0.0001470476,0.0001686407,0.0002159896,0.0002600186,0.006639354,0.009936718],"genre_scores_gemma":[0.6467121,0.0003900745,0.338576,0.0002314315,0.00008950886,0.0004109993,0.0004578815,0.0002495841,0.01288252],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005465678,"threshold_uncertainty_score":0.01828456,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006632534548773759,"score_gpt":0.2019202073934372,"score_spread":0.1952876728446634,"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."}}