{"id":"W4401164255","doi":"10.1109/bmsb62888.2024.10608208","title":"Cancelling Adjacent Channel Interference for In-Band Full-Duplex Communications","year":2024,"lang":"en","type":"article","venue":"","topic":"Full-Duplex Wireless Communications","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Communications Research Centre Canada","funders":"","keywords":"Interference (communication); Adjacent-channel interference; Duplex (building); Channel (broadcasting); Computer science; Co-channel interference; Telecommunications; Electronic engineering; Engineering; Chemistry","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":[0.0002508108,0.0003425456,0.00024437,0.0002441751,0.0003737244,0.0004489648,0.0003803839,0.0002708952,0.001223667],"category_scores_gemma":[0.0005538669,0.0001224377,0.0002371274,0.0002767441,0.0003415924,0.0004091634,0.0002880514,0.0004376747,0.0003778976],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003240291,"about_ca_system_score_gemma":0.0006221223,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001160562,"about_ca_topic_score_gemma":0.003161924,"domain_scores_codex":[0.9997513,0.00003855339,0.000007730234,0.00002253923,0.0001551935,0.00002474147],"domain_scores_gemma":[0.9997663,0.00008538699,0.00004167836,0.00002326578,0.00007259074,0.00001079627],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002668749,0.0002247621,0.004268019,0.0006140193,0.0001385769,0.0003926019,0.0004766093,0.1946838,0.4343248,0.03000672,0.002728937,0.3318743],"study_design_scores_gemma":[0.00002198294,0.0003608936,0.001062886,0.00002583737,0.00006046671,0.0004186113,0.00005637247,0.8712592,0.1170551,0.002096649,0.007554265,0.00002777274],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07693177,0.0007490905,0.911491,0.0001026568,0.00009451269,0.00004331148,0.00002656174,0.0004133434,0.01014782],"genre_scores_gemma":[0.90025,0.0006379805,0.09579711,0.00009715427,0.00004838653,0.00002526252,0.00004935023,0.00002439582,0.003070213],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001223667,"threshold_uncertainty_score":0.004093528,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04609926919157514,"score_gpt":0.282862621523485,"score_spread":0.2367633523319099,"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."}}