{"id":"W2170095549","doi":"10.1109/aps.2010.5562300","title":"A miniaturized multiband monopole antenna using a double-tuned wheeler matching network","year":2010,"lang":"en","type":"article","venue":"","topic":"Antenna Design and Analysis","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Broadband; Antenna (radio); Matching (statistics); Monopole antenna; Dipole antenna; Computer science; Transmission line; Physics; Electrical length; Electrical engineering; Electronic engineering; Topology (electrical circuits); Telecommunications; Engineering; Antenna efficiency; 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":[0.0001569301,0.000582531,0.0006906057,0.0003315323,0.000156256,0.0005538316,0.001427444,0.001123403,0.001613144],"category_scores_gemma":[0.0002157492,0.0003772038,0.000543043,0.0006274562,0.0002429897,0.000691167,0.0004657679,0.0003187259,0.001735773],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004997591,"about_ca_system_score_gemma":0.0002327798,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002556764,"about_ca_topic_score_gemma":0.0003309453,"domain_scores_codex":[0.9997391,0.00003840834,0.0000127222,0.00009105626,0.00007956928,0.00003907201],"domain_scores_gemma":[0.9998035,0.00002898949,0.00005359641,0.0000474265,0.00004492529,0.00002160771],"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":[0.0003164504,0.00006779304,0.0006726781,0.0001895923,0.00006889208,0.0002738925,0.00004058516,0.006808255,0.9067206,0.00612736,0.002120134,0.07659388],"study_design_scores_gemma":[0.0001477167,0.001283116,0.003090073,0.00003606136,0.0001713576,0.002790295,0.00004372348,0.1978697,0.7480796,0.001439718,0.04491347,0.0001351835],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1319753,0.0007288341,0.8505473,0.0003606277,0.0003746132,0.0001166163,0.0001550643,0.002814785,0.01292689],"genre_scores_gemma":[0.6567979,0.0004296998,0.330444,0.0003411986,0.00008023567,0.0001247909,0.0002120088,0.0001072719,0.01146284],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001613144,"threshold_uncertainty_score":0.005396485,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01430887459602442,"score_gpt":0.2280037171640172,"score_spread":0.2136948425679928,"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."}}