{"id":"W4220831932","doi":"10.3390/electronics11060959","title":"Harvesting Systems for RF Energy: Trends, Challenges, Techniques, and Tradeoffs","year":2022,"lang":"en","type":"article","venue":"Electronics","topic":"Energy Harvesting in Wireless Networks","field":"Engineering","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Rectenna; Rectifier (neural networks); Radio frequency; Bandwidth (computing); Energy harvesting; Wireless; Electronic engineering; Electrical engineering; Computer science; Power management; RF power amplifier; Power (physics); Engineering; Telecommunications; Physics","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":[0.001492822,0.000422697,0.0005024212,0.0009738554,0.0003601199,0.00199629,0.0008590144,0.00109672,0.002403282],"category_scores_gemma":[0.000960637,0.0003630182,0.0004351655,0.001482758,0.000646588,0.003672865,0.0008881819,0.001640994,0.001255536],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005652533,"about_ca_system_score_gemma":0.0003304185,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002356669,"about_ca_topic_score_gemma":0.0005371748,"domain_scores_codex":[0.999468,0.0001033512,0.00004028038,0.000107159,0.0002410656,0.00004016963],"domain_scores_gemma":[0.9994885,0.0002872897,0.00004074436,0.00005072411,0.0001147404,0.00001796542],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001244746,0.0001306054,0.001486939,0.005225606,0.00008378948,0.0004081146,0.0008550262,0.01033176,0.0973338,0.1880516,0.007150449,0.6888177],"study_design_scores_gemma":[0.00002073218,0.0008197271,0.002185209,0.002073994,0.0001237692,0.002763855,0.001467425,0.03070953,0.07925812,0.104102,0.7763039,0.0001716389],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.03023341,0.7233306,0.1671502,0.00701219,0.0008429471,0.0001205285,0.0001652606,0.0003617941,0.07078302],"genre_scores_gemma":[0.1945626,0.6706346,0.1107745,0.001869582,0.001209256,0.000203302,0.0002948862,0.0001773122,0.02027402],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.002403282,"threshold_uncertainty_score":0.008039832,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01462093172008196,"score_gpt":0.2046291975388098,"score_spread":0.1900082658187278,"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."}}