{"id":"W4387938008","doi":"10.1017/s1759078723001162","title":"Efficient rectifier circuit operating at N78 and N79 sub-6 GHz 5G bands for microwave energy-harvesting and power transfer applications","year":2023,"lang":"en","type":"article","venue":"International Journal of Microwave and Wireless Technologies","topic":"Energy Harvesting in Wireless Networks","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Military College of Canada; Concordia University","funders":"","keywords":"Rectifier (neural networks); Microwave; Precision rectifier; Wireless power transfer; Multi-band device; Impedance matching; Optoelectronics; Energy conversion efficiency; Materials science; Microwave transmission; Bottleneck; Electrical engineering; Electronic engineering; Electrical impedance; Computer science; Voltage; Telecommunications; Engineering; Wireless; Antenna (radio); Power factor","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":[0.0001990804,0.0002389979,0.0003663365,0.000201217,0.0001539969,0.0004074308,0.0006988245,0.0005489701,0.003672978],"category_scores_gemma":[0.0002918786,0.0001103249,0.0003236762,0.0003044803,0.0001558396,0.0006125476,0.000237674,0.0003136332,0.001657124],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003070157,"about_ca_system_score_gemma":0.0001557401,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001076272,"about_ca_topic_score_gemma":0.0002160108,"domain_scores_codex":[0.9997526,0.00002923544,0.00001930089,0.00006364893,0.0001017549,0.0000334876],"domain_scores_gemma":[0.9997827,0.00003530029,0.00007385522,0.00003362972,0.00006438192,0.00001008278],"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":[0.0001079049,0.00004265385,0.0004405488,0.0002034562,0.00002229064,0.0001232433,0.00005392929,0.000845355,0.9791708,0.001827059,0.001451918,0.01571091],"study_design_scores_gemma":[0.00004981238,0.0004228705,0.001510457,0.00002823591,0.00004587361,0.0005137579,0.00003746449,0.01580649,0.9675493,0.0005675592,0.01344869,0.00001936405],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7563098,0.001847262,0.1995502,0.001008708,0.0005276552,0.0002483948,0.0008214476,0.002198744,0.03748795],"genre_scores_gemma":[0.9783283,0.0002465186,0.01677274,0.0001281306,0.00003312036,0.00004475671,0.0001457578,0.00005531061,0.004245469],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003672978,"threshold_uncertainty_score":0.01228738,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01153945110813326,"score_gpt":0.218775508978543,"score_spread":0.2072360578704098,"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."}}