{"id":"W3035773905","doi":"10.3390/app10124123","title":"Understanding Digital Radio Frequency Memory Performance in Countermeasure Design","year":2020,"lang":"en","type":"article","venue":"Applied Sciences","topic":"Radar Systems and Signal Processing","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Military College of Canada","funders":"","keywords":"Digital radio frequency memory; Field-programmable gate array; Transmitter; Software-defined radio; Computer science; Computer hardware; Electronic engineering; Wideband; Radio frequency; Embedded system; Radar; Electrical engineering; Engineering; Telecommunications; Pulse-Doppler radar; Radar imaging","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":[],"consensus_categories":[],"category_scores_codex":[0.0002742078,0.0001000442,0.0001250589,0.00005344709,0.000126166,0.0001933432,0.0002112966,0.00003469694,0.00001075999],"category_scores_gemma":[0.000008604943,0.00008740151,0.00001449771,0.0004247997,0.00009952077,0.0004253595,0.00001054291,0.0001063669,0.00002311827],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008015833,"about_ca_system_score_gemma":0.0000438215,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001474379,"about_ca_topic_score_gemma":0.000001472366,"domain_scores_codex":[0.9991809,0.000005957051,0.0001658129,0.0001763709,0.0002492335,0.0002217355],"domain_scores_gemma":[0.9998295,0.00003314988,0.00002220553,0.00004879193,0.000005311409,0.00006107094],"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":[0.00002953875,0.00002451174,0.01313359,0.0006670589,0.00003351446,0.00004221508,0.01253491,0.8798344,0.07271632,0.007995982,0.001957374,0.01103063],"study_design_scores_gemma":[0.0008257661,0.0001666962,0.001387795,0.0002527703,0.000008668339,0.00002376588,0.007490164,0.9738199,0.01147425,0.003154024,0.0004676301,0.0009286168],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4210442,0.0009727696,0.3590755,0.000193439,0.0003214896,0.0003942982,0.000003227443,0.0004370311,0.217558],"genre_scores_gemma":[0.9992688,0.000008292013,0.0005849475,0.00005406267,0.00006230784,0.000006376681,3.654635e-7,0.0000096082,0.000005266438],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5782245,"threshold_uncertainty_score":0.356413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1116516492517885,"score_gpt":0.2104511088536028,"score_spread":0.09879945960181433,"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."}}