{"id":"W2893722414","doi":"10.1109/tmtt.2018.2868941","title":"Nonuniformly Distributed Electronic Impedance Synthesizer","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Microwave Theory and Techniques","topic":"Advanced MEMS and NEMS Technologies","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Polytechnique Montréal","funders":"","keywords":"Impedance matching; Electronic engineering; Electrical impedance; Smith chart; Figure of merit; Particle swarm optimization; Computer science; Matching (statistics); Output impedance; Engineering; Electrical engineering; Algorithm; 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":[0.0001820779,0.0001901105,0.0001563278,0.0001078515,0.0001609544,0.0000190937,0.00012272,0.0001470272,0.00004260878],"category_scores_gemma":[0.000005259239,0.0001729703,0.00005233522,0.0001558019,0.000263775,0.0001365824,0.000001488376,0.0003063737,0.00001761576],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000592014,"about_ca_system_score_gemma":0.000009398603,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001679207,"about_ca_topic_score_gemma":0.00001732984,"domain_scores_codex":[0.9992928,0.00001401033,0.0001434718,0.0001840301,0.00005090766,0.0003147709],"domain_scores_gemma":[0.9995649,0.00009680862,0.00002099252,0.0002495328,0.0000307742,0.00003694605],"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":[0.00006023028,0.00001979314,1.349947e-7,0.00001481475,0.0000295643,0.000001634979,0.00004039827,0.00001045073,0.8636941,0.005713691,0.00007650868,0.1303387],"study_design_scores_gemma":[0.00007686416,0.0001916545,0.000002146524,0.00004437973,0.00001896603,0.00002567074,0.0000518911,0.00002119842,0.9501004,0.04314797,0.006118914,0.0002000129],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2852824,0.0001609997,0.7113923,0.00001983642,0.00006729816,0.0001421552,0.00003326436,0.001790961,0.00111073],"genre_scores_gemma":[0.9951516,0.00123842,0.003268417,0.00004670658,0.00003339091,0.00006274262,0.000001575099,0.0000351022,0.0001620268],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7098692,"threshold_uncertainty_score":0.7053524,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004648959474593767,"score_gpt":0.2178646308304973,"score_spread":0.2132156713559036,"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."}}