{"id":"W4411640094","doi":"10.1109/lwc.2025.3583270","title":"Near-Field Energy Harvesting Using XL-MIMO Over Non-Stationary Channels","year":2025,"lang":"en","type":"article","venue":"IEEE Wireless Communications Letters","topic":"Energy Harvesting in Wireless Networks","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"European Research Council; Engineering and Physical Sciences Research Council; European Commission; Queen's University; Queen's University Belfast; Department for the Economy; UK Research and Innovation","keywords":"Energy harvesting; MIMO; Energy (signal processing); Computer science; Field (mathematics); Channel (broadcasting); Telecommunications; Physics; Mathematics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002041761,0.0003312476,0.0003177726,0.0002573505,0.0006303304,0.0002349215,0.001311718,0.000189622,0.00001291073],"category_scores_gemma":[0.00004515667,0.0004130739,0.000110596,0.0008730165,0.0002232047,0.0004083634,0.0002480467,0.0005705459,0.000009703658],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002159016,"about_ca_system_score_gemma":0.00007435943,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007830538,"about_ca_topic_score_gemma":0.00017574,"domain_scores_codex":[0.998305,0.0001384925,0.0005517473,0.000305473,0.0002081408,0.0004911678],"domain_scores_gemma":[0.9969485,0.000907355,0.0001137404,0.001845505,0.00008963093,0.00009527697],"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":[0.000004663862,0.0000395762,0.001224941,0.00006198705,0.000133212,0.00000822715,0.0002144897,0.9372599,0.03915858,0.002887821,0.008903886,0.01010276],"study_design_scores_gemma":[0.0002955265,0.000007125037,0.0005990888,0.0004898286,0.00004080169,0.000008397904,0.00003674761,0.9836313,0.005078052,0.00009573977,0.009310887,0.0004064828],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6077616,0.0006677008,0.3816721,0.002077311,0.001661668,0.0001731279,0.00001038984,0.0008474272,0.005128664],"genre_scores_gemma":[0.9757372,0.000242828,0.02018842,0.003102164,0.0001790493,0.0001144672,0.00005891257,0.00009168781,0.0002852727],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3679756,"threshold_uncertainty_score":0.9998321,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0167477046907739,"score_gpt":0.2548768533998469,"score_spread":0.238129148709073,"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."}}