{"id":"W4407825994","doi":"10.1109/tccn.2025.3544838","title":"CNN-Aided Self-Interference Estimation for In-Band Full-Duplex Systems","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Cognitive Communications and Networking","topic":"Full-Duplex Wireless Communications","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Communications Research Centre Canada","funders":"Eusko Jaurlaritza; European Regional Development Fund; Euskal Herriko Unibertsitatea; Agencia Estatal de Investigación; CHIST-ERA; European Commission","keywords":"Computer science; Interference (communication); Telecommunications; Electronic engineering; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002639937,0.0002305031,0.0002740261,0.0003720251,0.0005730303,0.0001307476,0.0004560898,0.0001330947,0.000005342918],"category_scores_gemma":[0.00001161122,0.0002692023,0.00007205812,0.0006324296,0.0001237282,0.0001871528,0.000009651098,0.0003717144,0.000007201879],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000153359,"about_ca_system_score_gemma":0.00004400458,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004285665,"about_ca_topic_score_gemma":0.0005180933,"domain_scores_codex":[0.9987968,0.0001407379,0.0004713587,0.0002348797,0.0000799597,0.000276295],"domain_scores_gemma":[0.9970145,0.001884542,0.00006583799,0.0008044933,0.0001739659,0.00005667611],"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":[0.00009388007,0.0003624783,0.0001132029,0.0003168536,0.0003170187,5.735341e-7,0.001254963,0.7737604,0.001482667,0.001473439,0.0001252068,0.2206994],"study_design_scores_gemma":[0.0008378616,0.00005507431,0.0001401947,0.001200437,0.0001006917,0.000003864087,0.0004819563,0.9949709,0.0006954091,0.00004488434,0.001229628,0.0002391396],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06648894,0.005064655,0.9247544,0.0002515628,0.0005236823,0.001070002,0.00006167362,0.0004146727,0.001370449],"genre_scores_gemma":[0.9862284,0.00816055,0.004098212,0.00005577186,0.00002216127,0.001271236,0.00004607642,0.00003465834,0.00008289945],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9206561,"threshold_uncertainty_score":0.999976,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.028847795194744,"score_gpt":0.2779536982918908,"score_spread":0.2491059030971468,"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."}}