{"id":"W3200813303","doi":"10.1007/s42979-022-01022-2","title":"An Empirical Study on Using CNNs for Fast Radio Signal Prediction","year":2022,"lang":"en","type":"article","venue":"SN Computer Science","topic":"Wireless Signal Modulation Classification","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"Communications Research Centre Canada; Toronto Metropolitan University","funders":"","keywords":"Overfitting; Computer science; Deep learning; Artificial intelligence; Machine learning; Predictive modelling; Segmentation; Frame (networking); Process (computing); Pattern recognition (psychology); Artificial neural network; Telecommunications","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":[0.003705937,0.0009594474,0.0003830297,0.0007840807,0.0003445144,0.0009323072,0.001007387,0.001095724,0.00289435],"category_scores_gemma":[0.02536505,0.0002741455,0.0004756382,0.0008844908,0.0004883154,0.002577925,0.0006181196,0.001025717,0.0006345335],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008147815,"about_ca_system_score_gemma":0.0004796131,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01114799,"about_ca_topic_score_gemma":0.01181658,"domain_scores_codex":[0.9985608,0.000629679,0.0001214875,0.0002716988,0.0002667225,0.0001494803],"domain_scores_gemma":[0.976688,0.01881658,0.0009912716,0.001587569,0.001714199,0.00020238],"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":[0.002342026,0.001663891,0.3041048,0.0007322947,0.0007335074,0.0005247573,0.0002507987,0.1509932,0.008040912,0.004957164,0.01228878,0.5133678],"study_design_scores_gemma":[0.00005101487,0.00062534,0.04451278,0.0001199832,0.0002437965,0.0004106338,0.0003146871,0.9412003,0.006963636,0.002541776,0.002986554,0.00002963465],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9696196,0.0034119,0.02038491,0.0007395039,0.000186908,0.00006361346,0.0009802396,0.000199943,0.00441341],"genre_scores_gemma":[0.9897461,0.0006039504,0.006297538,0.00009251498,0.00008104058,0.00001949572,0.001402614,0.00003217613,0.001724459],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01114799,"threshold_uncertainty_score":0.02216625,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07819158892404973,"score_gpt":0.3391232058734515,"score_spread":0.2609316169494018,"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."}}