{"id":"W4296354005","doi":"10.3390/mi13091533","title":"Novel Deep-Learning Modulation Recognition Algorithm Using 2D Histograms over Wireless Communications Channels","year":2022,"lang":"en","type":"article","venue":"Micromachines","topic":"Wireless Signal Modulation Classification","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Prince Sultan University; Princess Nourah Bint Abdulrahman University","keywords":"Computer science; Deep learning; Wireless; Artificial intelligence; Modulation (music); Algorithm; Pattern recognition (psychology); Electronic engineering; Telecommunications; Engineering; Physics; Acoustics","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":["sts"],"consensus_categories":[],"category_scores_codex":[0.0004509936,0.0001998668,0.0001889605,0.0002977645,0.001348072,0.0001973353,0.00106775,0.00006211764,0.00004305301],"category_scores_gemma":[0.00002717951,0.0002382177,0.00009592184,0.0008719065,0.00006467302,0.0006888636,0.00072107,0.000392193,0.00001687773],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000377042,"about_ca_system_score_gemma":0.00004690765,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004475833,"about_ca_topic_score_gemma":0.00002008457,"domain_scores_codex":[0.9981167,0.0003292933,0.0004087149,0.000483697,0.0003979794,0.0002635784],"domain_scores_gemma":[0.9984427,0.0001303119,0.0003735805,0.0008166584,0.0001653083,0.00007140514],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000006611921,0.0003379214,0.0009200577,0.00001445118,0.00003185283,0.000001943035,0.001689633,0.0438162,0.4111843,0.001868796,0.00005181424,0.5400765],"study_design_scores_gemma":[0.0003810984,0.00003928437,0.005533709,0.00001321704,0.00001292159,0.00005647661,0.00006785823,0.9901286,0.0007482175,0.0009630293,0.001768675,0.0002868531],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2010672,0.0001497069,0.7971533,0.0004163681,0.0004771656,0.0002511972,0.00001716124,0.0003961934,0.00007171084],"genre_scores_gemma":[0.8378851,0.000008741864,0.1613706,0.0001252352,0.00009172547,0.00008749548,0.0003326954,0.0000294007,0.0000688912],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9463125,"threshold_uncertainty_score":0.999952,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0515462477306602,"score_gpt":0.2766370654938706,"score_spread":0.2250908177632104,"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."}}