{"id":"W2809145887","doi":"10.1109/tvlsi.2018.2839709","title":"A 60-GHz Transmission Line Phase Shifter Using Varactors and Tunable Inductors in 65-nm CMOS Technology","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Very Large Scale Integration (VLSI) Systems","topic":"Radio Frequency Integrated Circuit Design","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Alberta Innovates - Technology Futures","keywords":"Phase shift module; Inductor; Varicap; Transmission line; Insertion loss; Transformer; CMOS; Return loss; Electrical engineering; Materials science; Optoelectronics; Electric power transmission; Electronic engineering; Engineering; Capacitance; Physics; Voltage; Electrode","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002058947,0.0002478051,0.0002223279,0.0002378479,0.0002056263,0.000462835,0.0005238129,0.0003957753,0.0008627754],"category_scores_gemma":[0.0002492936,0.0001598535,0.0002930393,0.0002808922,0.0002155109,0.0006555382,0.0002493526,0.0002986937,0.0005948016],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003093274,"about_ca_system_score_gemma":0.0003313924,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005047048,"about_ca_topic_score_gemma":0.000894793,"domain_scores_codex":[0.9997558,0.00002327539,0.00001714332,0.00006926188,0.00009201006,0.00004253327],"domain_scores_gemma":[0.9998934,0.00002047729,0.00003415971,0.00001354298,0.0000265763,0.00001180679],"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":[0.00008381803,0.00002720522,0.0004694809,0.0001004739,0.00001502779,0.0001687484,0.00008206908,0.0008729534,0.9633359,0.004867753,0.000555433,0.02942114],"study_design_scores_gemma":[0.0001120094,0.0007810402,0.001537472,0.00003315926,0.0001022949,0.00176301,0.00005779587,0.01991001,0.9188368,0.0009184555,0.05590288,0.0000449353],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4921455,0.003420083,0.4769284,0.0007223229,0.0005381614,0.0002173137,0.0002405861,0.002325762,0.02346176],"genre_scores_gemma":[0.7871141,0.0009852939,0.2036469,0.0002898245,0.0001082929,0.00005770539,0.0001617785,0.00009113908,0.00754491],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008627754,"threshold_uncertainty_score":0.002886295,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01991659639761929,"score_gpt":0.2609058176102396,"score_spread":0.2409892212126203,"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."}}