{"id":"W4408717432","doi":"10.1109/emts57498.2023.10925231","title":"Near-Field Sensing Improvement of a Radar AntennaOn-Chip Using a Transmissive Superstrate","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Antenna and Metasurface Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Infineon Technologies; Ansys; Hennepin County Medical Center","keywords":"Radar; Chip; Performance improvement; Field (mathematics); Materials science; Computer science; Electronic engineering; Telecommunications; Engineering","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":[0.00007318438,0.0001281213,0.0001910618,0.00008534614,0.00004660791,0.00001322213,0.00008107383,0.00005714896,0.00001845086],"category_scores_gemma":[0.00002681828,0.0001158017,0.00007003823,0.0003570696,0.00004707973,0.00008833896,0.00002053643,0.0001163998,0.00000763958],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001707774,"about_ca_system_score_gemma":0.00001604669,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005780763,"about_ca_topic_score_gemma":0.00001333813,"domain_scores_codex":[0.9992899,0.000004006141,0.0001959123,0.0001281165,0.0001009668,0.0002810878],"domain_scores_gemma":[0.9997061,0.00004236839,0.00002041632,0.0001673459,0.00002815406,0.00003565418],"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":[0.000006437885,0.000003604398,0.00003357792,0.00007264338,0.00003593645,0.00002106272,0.0002174512,0.005745775,0.9758617,0.0001008377,0.00004437143,0.01785659],"study_design_scores_gemma":[0.000242546,0.0000634176,0.00004704553,0.00006925236,0.00001975601,0.000006655497,0.002304893,0.1670277,0.8289146,0.0009384641,0.0001977935,0.0001678384],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8982731,0.000141644,0.0997573,0.00009423362,0.0001195728,0.0001101934,0.000005041568,0.0009767491,0.0005221887],"genre_scores_gemma":[0.9730093,0.0001675363,0.02670445,0.00002287653,0.000008819935,9.953308e-7,0.000001641282,0.00002439877,0.00005992288],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1612819,"threshold_uncertainty_score":0.4722258,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02259246114588283,"score_gpt":0.2455072211282494,"score_spread":0.2229147599823666,"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."}}