{"id":"W2580825565","doi":"10.1109/iccs.2016.7833576","title":"An anti-eavesdropping interference alignment scheme with wireless power transfer","year":2016,"lang":"en","type":"article","venue":"","topic":"Energy Harvesting in Wireless Networks","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Carleton University","funders":"","keywords":"Eavesdropping; Computer science; Transmitter; Interference (communication); Wireless power transfer; Transmitter power output; Artificial noise; Wireless; Energy (signal processing); Power (physics); Scheme (mathematics); Electronic engineering; Maximum power transfer theorem; Computer network; Telecommunications; Engineering; Physics; Mathematics; Channel (broadcasting)","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":[0.0005990789,0.0008807129,0.0005327709,0.0003977279,0.0004902644,0.0005058773,0.0009905268,0.0004998022,0.0007712568],"category_scores_gemma":[0.001027731,0.0001873085,0.0004127922,0.0007570491,0.0007794444,0.00122551,0.001179916,0.0006431954,0.0002436244],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003331187,"about_ca_system_score_gemma":0.0003542696,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000215138,"about_ca_topic_score_gemma":0.0002274949,"domain_scores_codex":[0.9993261,0.0002067092,0.00003833689,0.0001170833,0.0002354097,0.00007639216],"domain_scores_gemma":[0.9993837,0.0001960088,0.0001591768,0.0001098137,0.0001144437,0.00003677318],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008465031,0.0003382041,0.001941242,0.0004379017,0.000246373,0.001020085,0.0004718659,0.2253936,0.3880055,0.1071931,0.002641364,0.2714642],"study_design_scores_gemma":[0.00005856425,0.0006199089,0.0005626384,0.00002481983,0.00009644845,0.0008094046,0.00006550703,0.9003448,0.07756782,0.01567662,0.004122436,0.00005102091],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04339935,0.0003205677,0.9502529,0.0001702012,0.00006122218,0.0000647354,0.00002150907,0.0002072491,0.005502296],"genre_scores_gemma":[0.9025379,0.0004488713,0.0935766,0.0001878609,0.00007625082,0.0001090289,0.00003203393,0.00001881932,0.003012601],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0009905268,"threshold_uncertainty_score":0.003168285,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007851519725290511,"score_gpt":0.1963303454376484,"score_spread":0.1884788257123579,"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."}}