{"id":"W4387697135","doi":"10.1109/arftg57476.2023.10278907","title":"VNA-Based Characterization of Frequency Multipliers Phase-Distortions Under Continuous-Wave and Modulated Signal Excitation","year":2023,"lang":"en","type":"article","venue":"","topic":"Radio Frequency Integrated Circuit Design","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Frequency multiplier; Distortion (music); Phase distortion; SIGNAL (programming language); Phase (matter); Frequency modulation; Measure (data warehouse); Phase modulation; Continuous wave; Electronic engineering; Nonlinear distortion; Modulation (music); Excitation; Characterization (materials science); Computer science; Optics; Physics; Acoustics; CMOS; Engineering; Phase noise; Radio frequency; Electrical engineering; Telecommunications; Laser","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":[0.000119948,0.0001670914,0.0001994935,0.0003163237,0.00005311724,0.0000246246,0.0000595966,0.0001239307,0.0001627388],"category_scores_gemma":[0.00002710767,0.0001747967,0.00004617056,0.0006308822,0.00006747668,0.0002110939,0.000001082169,0.0001101345,0.00002578154],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001080859,"about_ca_system_score_gemma":0.000035858,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004100618,"about_ca_topic_score_gemma":0.00000867409,"domain_scores_codex":[0.9990315,0.00003698134,0.0003656398,0.0001878156,0.0001616316,0.0002163781],"domain_scores_gemma":[0.999516,0.00006795589,0.0000645749,0.0001602557,0.0001157239,0.00007554723],"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":[0.000004545318,0.0000273753,0.000219874,0.00003776665,0.00004976484,0.000005297635,0.0001835934,0.01635024,0.9797667,0.001356816,0.00009084229,0.001907178],"study_design_scores_gemma":[0.001229872,0.0000963358,0.01295239,0.00005274442,0.00004115625,0.000003871077,0.0001519866,0.704309,0.2787978,0.002051244,0.00002449278,0.000289055],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7557589,0.00002337735,0.240969,0.00003848074,0.000163863,0.000271319,0.00007079799,0.000761559,0.001942706],"genre_scores_gemma":[0.9989349,0.00001774569,0.0002986757,0.00002670634,0.00002304475,0.00004372972,0.0005034686,0.0000467502,0.0001049936],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7009689,"threshold_uncertainty_score":0.7128003,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02438051298837146,"score_gpt":0.2301200736079475,"score_spread":0.205739560619576,"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."}}