{"id":"W4308901339","doi":"10.48550/arxiv.2111.08928","title":"Achievable Rate of Near-Field Communications Based on Physically\\n Consistent Models","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Antenna Design and Analysis","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Division of Electrical, Communications and Cyber Systems; Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Reciprocity (cultural anthropology); Antenna (radio); Constraint (computer-aided design); Near and far field; Computer science; Coupling (piping); Transmitter; Topology (electrical circuits); Physics; Telecommunications; Mathematics; Electrical engineering; Engineering; Optics; Geometry","routes":{"ca_aff":true,"ca_fund":true,"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":[0.003098291,0.001650348,0.001869678,0.001341208,0.001190303,0.003251283,0.002257348,0.002053635,0.002968683],"category_scores_gemma":[0.01606569,0.0007380687,0.0008360544,0.001156373,0.003386098,0.004702243,0.00298311,0.002490127,0.0006838135],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002820214,"about_ca_system_score_gemma":0.001433667,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001121241,"about_ca_topic_score_gemma":0.0006802068,"domain_scores_codex":[0.9971442,0.001248027,0.00006896786,0.0003356976,0.0007980914,0.0004051273],"domain_scores_gemma":[0.9880243,0.009555959,0.0007168453,0.0009025791,0.000594157,0.0002060657],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009792224,0.00004523474,0.0002087285,0.0001144287,0.00003076806,0.0001064627,0.000149782,0.266387,0.002360263,0.7243978,0.001327771,0.004773724],"study_design_scores_gemma":[0.00001543969,0.00002923273,0.00007786232,0.00003897724,0.00001198909,0.00008760676,0.00004311155,0.7227681,0.001160554,0.2749512,0.0007865788,0.00002936141],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07856244,0.001329039,0.8702612,0.001899231,0.00009969573,0.00008049612,0.0004320334,0.0003503284,0.04698557],"genre_scores_gemma":[0.9659393,0.001142556,0.02706751,0.0003093078,0.0001344423,0.0002621271,0.0001966577,0.00009625945,0.004851846],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003251283,"threshold_uncertainty_score":0.02046216,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07888114158690383,"score_gpt":0.1805092539051427,"score_spread":0.1016281123182388,"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."}}