{"id":"W2787836236","doi":"10.1109/lsp.2018.2802780","title":"Is Self-Interference in Full-Duplex Communications a Foe or a Friend?","year":2018,"lang":"en","type":"article","venue":"IEEE Signal Processing Letters","topic":"Full-Duplex Wireless Communications","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Telecommunications link; Base station; Maximization; Transmission (telecommunications); Iterative method; Convex optimization","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001928624,0.0002774235,0.0002574673,0.0002603503,0.0002944821,0.0001683149,0.001503859,0.0001092553,0.0001475669],"category_scores_gemma":[0.00002146433,0.0002756218,0.00006057138,0.000810091,0.0003330274,0.0004294366,0.0001467109,0.000535736,0.0002004377],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002078633,"about_ca_system_score_gemma":0.00008999641,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005572644,"about_ca_topic_score_gemma":0.0003564819,"domain_scores_codex":[0.9984773,0.00008067939,0.0004733859,0.000295908,0.0001992163,0.0004734836],"domain_scores_gemma":[0.9984016,0.0001508906,0.00008937047,0.001139576,0.0001159632,0.0001025352],"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":[0.0001586572,0.0004894088,0.00101282,0.0006483817,0.0002015045,0.00003239504,0.0419382,0.07207666,0.805889,0.000132077,0.02922844,0.04819247],"study_design_scores_gemma":[0.0004593128,0.00006372629,0.0003022469,0.0003788064,0.00002432312,0.00002697251,0.0002945071,0.9842483,0.008585495,0.000009197866,0.005171884,0.0004351598],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.944352,0.0004790873,0.04763782,0.005085012,0.0002066285,0.0003358862,0.00002059128,0.001052753,0.0008301724],"genre_scores_gemma":[0.9796178,0.00005457609,0.01853861,0.001404882,0.0001273597,0.0001302076,0.00001029078,0.00007048927,0.000045825],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9121717,"threshold_uncertainty_score":0.9999696,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03871680295729976,"score_gpt":0.2793275456708534,"score_spread":0.2406107427135536,"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."}}