{"id":"W3131809952","doi":"10.1109/ieeeconf35879.2020.9330422","title":"Imaging of Walking Human Behind the Wall Using Impulse Radar","year":2020,"lang":"en","type":"article","venue":"","topic":"Microwave Imaging and Scattering Analysis","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Radar imaging; Radar; Computer vision; Computer science; Envelope (radar); Artificial intelligence; Radar lock-on; Impulse (physics); Continuous-wave radar; Radar tracker; Pulse-Doppler radar; Impulse response; Telecommunications; Physics; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001329188,0.0001203278,0.0001700283,0.00004806693,0.00009390832,0.00004774884,0.0002034656,0.00001673741,0.0001327171],"category_scores_gemma":[0.00001005048,0.00009207299,0.0001049614,0.0001332618,0.00003966583,0.00007245664,0.00004770757,0.000139425,0.000009580666],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002295378,"about_ca_system_score_gemma":0.000005400945,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002765572,"about_ca_topic_score_gemma":0.000009505996,"domain_scores_codex":[0.9993109,0.00002179805,0.0002321247,0.0001325054,0.0001135167,0.0001891658],"domain_scores_gemma":[0.9996666,0.00002268669,0.00003235829,0.0002030124,0.00002019762,0.0000551265],"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":[0.000001183985,0.000005118711,0.004129264,0.00007062013,0.00009359511,0.000007146468,0.002542309,0.01093075,0.9765636,0.00003595417,0.001226905,0.004393577],"study_design_scores_gemma":[0.0002552199,0.000008305926,0.001406922,0.00005223957,0.000147196,0.00001790088,0.0006421651,0.862674,0.1323939,0.00009127411,0.00198337,0.0003275179],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9625873,0.0004731143,0.0318171,0.001106563,0.00006453122,0.00005706069,0.000002989748,0.0002747693,0.003616591],"genre_scores_gemma":[0.9974153,0.0000059421,0.002125661,0.0003189332,0.00006727584,6.155669e-7,0.000002616453,0.00002829649,0.00003538283],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8517432,"threshold_uncertainty_score":0.3754628,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01602203361419296,"score_gpt":0.2298796819220524,"score_spread":0.2138576483078594,"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."}}