{"id":"W4403181869","doi":"10.1109/access.2024.3475732","title":"Deep Learning-Based Interference Detection, Classification, and Forecasting Algorithm for ESM Radar Systems","year":2024,"lang":"en","type":"article","venue":"IEEE Access","topic":"Advanced SAR Imaging Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Computer science; Radar; Interference (communication); Artificial intelligence; Statistical classification; Machine learning; Algorithm; Pattern recognition (psychology); 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":[0.000700816,0.0008766314,0.0007710934,0.0006518289,0.000316897,0.0006666016,0.001271918,0.0008734622,0.001418608],"category_scores_gemma":[0.001906991,0.0003196238,0.000480959,0.0006342992,0.0003009975,0.0007900625,0.0007801894,0.001550741,0.0005044006],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009334437,"about_ca_system_score_gemma":0.00117553,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008099517,"about_ca_topic_score_gemma":0.007048234,"domain_scores_codex":[0.9996654,0.00005170426,0.00002648021,0.00007970344,0.00009401883,0.00008270808],"domain_scores_gemma":[0.9994292,0.0002040294,0.00007614792,0.00003507476,0.000224041,0.00003155598],"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":[0.0001717148,0.0001528323,0.003902623,0.00009295525,0.00007116517,0.000100464,0.00006399154,0.5237937,0.005220061,0.003681165,0.00340344,0.4593458],"study_design_scores_gemma":[0.000002678209,0.00001171001,0.000126338,0.000002839867,0.000003788699,0.000007954206,0.00000320426,0.9986165,0.0005633786,0.0005027496,0.0001567747,0.000002123503],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03423369,0.0006408297,0.9615312,0.0004430475,0.00007084249,0.00004743112,0.00009796039,0.001097273,0.001837648],"genre_scores_gemma":[0.7721717,0.0004773241,0.2206704,0.0005077742,0.0001127993,0.0001693287,0.0005132518,0.00006680077,0.005310776],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008099517,"threshold_uncertainty_score":0.01610476,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03903382234752324,"score_gpt":0.2963216076022533,"score_spread":0.2572877852547301,"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."}}