{"id":"W2735283278","doi":"10.5515/kjkiees.2017.28.5.419","title":"A CMOS UWB RFIC Based Radar System for High Speed Target Detection","year":2017,"lang":"en","type":"article","venue":"The Journal of Korean Institute of Electromagnetic Engineering and Science","topic":"Non-Invasive Vital Sign Monitoring","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Meteorological and Oceanographic Society","funders":"Korea Evaluation Institute of Industrial Technology; Seoul National University of Science and Technology","keywords":"RFIC; CMOS; Radar; Bandwidth (computing); Electronic engineering; Chip; Radar systems; Envelope detector; Electrical engineering; Computer science; Engineering; Telecommunications; Amplifier","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":[0.0001901046,0.0003201716,0.0003941936,0.000311556,0.0002447025,0.0003543325,0.0005853443,0.0006112316,0.002158162],"category_scores_gemma":[0.0003034333,0.000192521,0.0001874148,0.0003148717,0.0001332691,0.0004443543,0.0002772025,0.0003811391,0.001254027],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002538757,"about_ca_system_score_gemma":0.0003443809,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002439933,"about_ca_topic_score_gemma":0.0003907806,"domain_scores_codex":[0.9997293,0.0000234193,0.00001568416,0.00006568563,0.0001394192,0.00002640529],"domain_scores_gemma":[0.9998418,0.00001912502,0.00002843223,0.00001574583,0.00007875175,0.00001602492],"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":[0.000189086,0.00007827987,0.0009676647,0.0004124129,0.00003056432,0.0004311008,0.0001025909,0.0009195391,0.8459225,0.003034147,0.004219642,0.1436925],"study_design_scores_gemma":[0.000143911,0.00183497,0.005494609,0.00009845918,0.0001912872,0.008001214,0.00006774523,0.02780502,0.8648139,0.0007904642,0.09068525,0.00007331009],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1337355,0.009381525,0.8042629,0.001408124,0.001203549,0.0005241422,0.000572593,0.006236651,0.04267505],"genre_scores_gemma":[0.6463976,0.003206342,0.3246254,0.001559355,0.000377248,0.0002137418,0.000532241,0.0001045879,0.02298342],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002158162,"threshold_uncertainty_score":0.007219791,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007488697805455543,"score_gpt":0.2004592658429613,"score_spread":0.1929705680375058,"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."}}