{"id":"W4300960895","doi":"10.52953/xbpt2357","title":"RFNet: Fast and efficient neural network for modulation classification of radio frequency signals","year":2022,"lang":"en","type":"article","venue":"ITU Journal on Future and Evolving Technologies","topic":"Wireless Signal Modulation Classification","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Pointwise; Modulation (music); Convolutional neural network; Artificial neural network; SIGNAL (programming language); Convolution (computer science); Algorithm; Computer engineering; Artificial intelligence; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005245674,0.0001324989,0.0001833799,0.0002288758,0.0006208165,0.0001236541,0.0004110544,0.0000900388,0.000004606794],"category_scores_gemma":[0.0000895081,0.0001176549,0.00005117694,0.0004203549,0.00007233371,0.0002550713,0.0001600096,0.0003123782,2.964381e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000924116,"about_ca_system_score_gemma":0.00002757219,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001666098,"about_ca_topic_score_gemma":8.658178e-7,"domain_scores_codex":[0.9987751,0.00007936968,0.0003512292,0.0002909848,0.0003038155,0.0001994975],"domain_scores_gemma":[0.998991,0.0001578335,0.0004421651,0.0002767399,0.00009810894,0.00003422036],"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":[0.00007228628,0.0001436835,0.009098706,0.00004371891,0.00005379747,0.000006081002,0.0008260505,0.4114211,0.03827494,0.1367603,0.004153593,0.3991457],"study_design_scores_gemma":[0.0003278519,0.000385868,0.05454667,0.00002612495,0.00001099129,0.00007378987,0.000470331,0.9161507,0.0004325042,0.02679721,0.0006218316,0.0001561185],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5012954,0.002437851,0.4821869,0.01252062,0.0007418756,0.0004144009,0.000006263226,0.0003291143,0.00006760427],"genre_scores_gemma":[0.9733483,0.00007149736,0.02633497,0.00004385126,0.0001369582,0.00003969477,0.000004504396,0.000009287941,0.00001096393],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5047296,"threshold_uncertainty_score":0.4797827,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02156078212384268,"score_gpt":0.2422941194134349,"score_spread":0.2207333372895922,"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."}}