{"id":"W4404035675","doi":"10.1109/lwc.2024.3490856","title":"Beyond Shannon Capacity: Deep Semantic Communication for Enhanced Performance in Impulsive Noise Environments","year":2024,"lang":"en","type":"article","venue":"IEEE Wireless Communications Letters","topic":"Music Technology and Sound Studies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Computer science; Noise (video); Computer network; Artificial intelligence","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":[0.001218226,0.0006627476,0.0005319635,0.0003903673,0.0005340888,0.001185221,0.0008436385,0.0008808857,0.002147363],"category_scores_gemma":[0.004254183,0.0001685994,0.000205561,0.0003776491,0.001577076,0.002262483,0.001734328,0.001171194,0.0003353721],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006505735,"about_ca_system_score_gemma":0.0008080928,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005780441,"about_ca_topic_score_gemma":0.001086692,"domain_scores_codex":[0.9995139,0.0001522808,0.00002038968,0.00005309663,0.0001783483,0.00008198067],"domain_scores_gemma":[0.9980878,0.001111501,0.0001425954,0.0002619886,0.0002849319,0.0001111497],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005944544,0.0001957923,0.001893051,0.0004967571,0.00008341041,0.0003845992,0.0005762469,0.4360733,0.1004207,0.3075981,0.00444353,0.1472401],"study_design_scores_gemma":[0.00001527727,0.0002690949,0.0002957835,0.00005402591,0.00002721401,0.000224482,0.0001108176,0.8676652,0.03353834,0.09438116,0.003375561,0.00004309816],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1903588,0.001054627,0.7829578,0.0009702907,0.000144715,0.00004645396,0.0001566761,0.0008782455,0.02343243],"genre_scores_gemma":[0.9745986,0.0002837099,0.02357572,0.0001763077,0.00003710779,0.00002226685,0.00003672507,0.00004123951,0.00122838],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002147363,"threshold_uncertainty_score":0.007183671,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01716767485965804,"score_gpt":0.2447198463862169,"score_spread":0.2275521715265588,"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."}}