{"id":"W2885018983","doi":"10.3390/electronics7070125","title":"An Adaptive Power Harvester with Active Load Modulation for Highly Efficient Short/Long Range RF WPT Applications","year":2018,"lang":"en","type":"article","venue":"Electronics","topic":"Energy Harvesting in Wireless Networks","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; University of Ottawa","funders":"","keywords":"Rectifier (neural networks); Wireless power transfer; Power (physics); Electronic engineering; Modulation (music); Radio frequency; Electrical engineering; Wireless; Energy conversion efficiency; ISM band; dBm; Range (aeronautics); Computer science; Engineering; Antenna (radio); Telecommunications; Physics; CMOS; Acoustics","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":[0.0002225214,0.0001614408,0.0002233914,0.0001311542,0.0001156379,0.0003661428,0.0006379009,0.000419372,0.0009510195],"category_scores_gemma":[0.0003082508,0.0001525023,0.0002455647,0.0002414597,0.0002001018,0.0008069901,0.0002443765,0.0003866992,0.0004437304],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001848499,"about_ca_system_score_gemma":0.00009059301,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000695682,"about_ca_topic_score_gemma":0.0001665505,"domain_scores_codex":[0.9998857,0.00001339613,0.000008487111,0.00003478577,0.00004838387,0.000009295108],"domain_scores_gemma":[0.9998869,0.00003873251,0.00002325049,0.00001973115,0.00002676393,0.000004601962],"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":[0.00004548542,0.00002571853,0.0001391879,0.000109472,0.00001167092,0.00005294643,0.00005915327,0.001658064,0.9777295,0.001656134,0.000270608,0.01824217],"study_design_scores_gemma":[0.00002656932,0.0003558567,0.0006791039,0.00001759149,0.00003908937,0.0003751556,0.00002266158,0.04851728,0.9339213,0.0006870621,0.01533585,0.00002250806],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4722458,0.002440297,0.512046,0.000514874,0.0002418758,0.000174596,0.0001596745,0.0009297645,0.01124721],"genre_scores_gemma":[0.9288894,0.0006208066,0.06449679,0.0001155891,0.00003992269,0.0000615263,0.00005683332,0.00006052334,0.005658604],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0009510195,"threshold_uncertainty_score":0.003181458,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00799374721206648,"score_gpt":0.2240096688190381,"score_spread":0.2160159216069716,"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."}}