{"id":"W2909911312","doi":"10.1109/apusncursinrsm.2018.8608914","title":"A 60-GHz Gain Enhanced Vivaldi Antenna On-Chip","year":2018,"lang":"en","type":"article","venue":"","topic":"Antenna Design and Analysis","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Vivaldi antenna; Antenna (radio); Antenna efficiency; Radiation pattern; Antenna factor; Antenna measurement; Optics; Antenna gain; Antenna aperture; Materials science; Coaxial antenna; Optoelectronics; Physics; Electrical engineering; Engineering","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00007821034,0.0001345202,0.0001591049,0.0000905724,0.00005094495,0.00002630207,0.0001255979,0.00005093007,0.001067907],"category_scores_gemma":[0.00001876496,0.000109351,0.00008957654,0.0002343053,0.00004460232,0.00005576189,0.00001280136,0.00008384292,0.002526049],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002043201,"about_ca_system_score_gemma":0.000005252583,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001048526,"about_ca_topic_score_gemma":0.00001991801,"domain_scores_codex":[0.9993254,0.00001280758,0.0001393767,0.0001565674,0.0001148522,0.0002509821],"domain_scores_gemma":[0.9996148,0.00002708145,0.00001184899,0.0002309299,0.00003508422,0.00008022427],"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":[0.00001690434,0.00003107101,0.00005202965,0.00001528438,0.0001179842,0.00001403666,0.0003097575,0.0001300306,0.9910478,0.000897778,0.004781256,0.002586096],"study_design_scores_gemma":[0.0004319679,0.0001815649,0.0005614297,0.00006373003,0.00004257666,0.000003626536,0.0003017024,0.8810229,0.1134776,0.0006617115,0.002754497,0.0004967266],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1263781,0.00006336298,0.7740582,0.0001498098,0.0002291688,0.00007819834,0.000003123367,0.0007164901,0.09832357],"genre_scores_gemma":[0.992224,0.0000329685,0.001063434,0.0004030242,0.0002432449,0.000005003131,0.000003049831,0.00002591927,0.005999387],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8808929,"threshold_uncertainty_score":0.9998453,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01293619148054106,"score_gpt":0.2238673275377238,"score_spread":0.2109311360571827,"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."}}