{"id":"W4312650432","doi":"10.1109/pimrc54779.2022.9977756","title":"Wireless Power Transfer Aided with Reconfigurable Intelligent Surfaces: Design, and Coverage Analysis","year":2022,"lang":"en","type":"article","venue":"2022 IEEE 33rd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Wireless power transfer; Computer science; Beamforming; Wireless; Maximum power transfer theorem; Stochastic geometry; Power (physics); Wireless network; Channel (broadcasting); Transmission (telecommunications); Energy (signal processing); Electronic engineering; Topology (electrical circuits); Computer network; Electrical engineering; Telecommunications; Engineering; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004004997,0.0003659169,0.0004431414,0.0004833473,0.0007214468,0.0001256337,0.00140725,0.0001050974,0.0003904004],"category_scores_gemma":[0.000012162,0.0003736085,0.0001300339,0.0008194064,0.0003529812,0.000383955,0.0002326977,0.0008730043,0.000007436508],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003738415,"about_ca_system_score_gemma":0.00004012324,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000678344,"about_ca_topic_score_gemma":0.00005939903,"domain_scores_codex":[0.9980004,0.0002578759,0.0004890584,0.0004589149,0.0004769599,0.0003167315],"domain_scores_gemma":[0.9978652,0.0005927083,0.00009897382,0.001159967,0.0001620081,0.0001211326],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00054979,0.0009600951,0.002691483,0.00006431798,0.003805252,0.00002061939,0.01565239,0.9258601,0.0182385,0.005659296,0.002063552,0.02443458],"study_design_scores_gemma":[0.004016263,0.002298967,0.001878036,0.0001701803,0.0006790557,0.0002543742,0.03145821,0.6565676,0.02583975,0.0004028362,0.2736655,0.002769183],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.919872,0.006155827,0.06226774,0.002626329,0.0004185524,0.001580451,0.001581266,0.0009459175,0.004551899],"genre_scores_gemma":[0.9805462,0.01587134,0.001164466,0.0001812604,0.00001382086,0.001358489,0.0002840297,0.00006544576,0.0005149761],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.271602,"threshold_uncertainty_score":0.9998716,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01396434758064127,"score_gpt":0.2409758544360977,"score_spread":0.2270115068554564,"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."}}