{"id":"W4312883044","doi":"10.1109/mbits.2022.3212978","title":"Role of Deep Learning in Wireless Communications","year":2022,"lang":"en","type":"article","venue":"IEEE BITS the Information Theory Magazine","topic":"Wireless Signal Modulation Classification","field":"Computer Science","cited_by":69,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Computer science; Wireless; Telecommunications; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001329447,0.0007887618,0.0006156605,0.0003648195,0.0002779072,0.001622863,0.0008206825,0.0012593,0.001210529],"category_scores_gemma":[0.004402384,0.0003630538,0.000241927,0.0005890931,0.001766794,0.002546333,0.001167111,0.003692951,0.0004195707],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008973731,"about_ca_system_score_gemma":0.0006583341,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002028075,"about_ca_topic_score_gemma":0.00155008,"domain_scores_codex":[0.9995381,0.0001757529,0.00002061379,0.00007790454,0.0001493107,0.00003840856],"domain_scores_gemma":[0.9986327,0.0009573643,0.0000707736,0.000135403,0.0001574171,0.00004621897],"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":[0.0001028149,0.00007891445,0.0009916992,0.0002741654,0.0001017555,0.00006714432,0.00008703477,0.5505604,0.004199735,0.2171612,0.005185405,0.2211897],"study_design_scores_gemma":[0.000005671675,0.00003059355,0.0001377995,0.00003502279,0.000007133692,0.00001575695,0.00001046246,0.9008992,0.001440561,0.09318212,0.004225228,0.00001041008],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.01592332,0.01126679,0.953649,0.006373951,0.0003573775,0.00002246654,0.0001017269,0.0004677945,0.01183754],"genre_scores_gemma":[0.7732641,0.01761102,0.1956067,0.001721247,0.0009549928,0.0001022334,0.0002163268,0.0001696181,0.01035379],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.002028075,"threshold_uncertainty_score":0.007030904,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01268347238545453,"score_gpt":0.2303713002553514,"score_spread":0.2176878278698968,"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."}}