{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000254013,0.0004489804,0.0003532429,0.0003433871,0.0001659049,0.0003556752,0.000588687,0.0003726039,0.001605595],"category_scores_gemma":[0.0005624037,0.0001437718,0.0001997929,0.0003153452,0.0002437566,0.0005491315,0.0004042995,0.0002851608,0.0004140275],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005399573,"about_ca_system_score_gemma":0.0001916941,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001935063,"about_ca_topic_score_gemma":0.0004013237,"domain_scores_codex":[0.9996049,0.00004927394,0.00002023335,0.0001500497,0.0001509722,0.00002462975],"domain_scores_gemma":[0.9996864,0.00005635964,0.00009664769,0.00007359542,0.00007155509,0.00001556201],"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":[0.0002315647,0.00008182742,0.001014012,0.0001392213,0.00003097643,0.0001398536,0.00008554562,0.040477,0.8272112,0.01212766,0.001062332,0.1173989],"study_design_scores_gemma":[0.0001103175,0.0007224706,0.001834642,0.00001617146,0.00005677,0.0004057629,0.00003062488,0.4189782,0.5552945,0.002228596,0.02027765,0.00004435932],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.189956,0.0004185103,0.7943211,0.0002313546,0.0001012509,0.0001358751,0.000197802,0.001581873,0.01305622],"genre_scores_gemma":[0.8261452,0.0001119703,0.1692082,0.00007231332,0.00004092063,0.00007989499,0.0001283408,0.00005702991,0.00415604],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001605595,"threshold_uncertainty_score":0.005371273,"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."}}