{"id":"W4389537350","doi":"10.1109/taes.2023.3308549","title":"Adaptive Beam Scheduling for Cooperative Phased Array Radars With High-Precision Pencil-Beam","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Aerospace and Electronic Systems","topic":"Radar Systems and Signal Processing","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Beamwidth; Phased array; Radar; Computer science; Mathematical optimization; Scheduling (production processes); Radar tracker; Algorithm; Real-time computing; Control theory (sociology); Electronic engineering; Engineering; Mathematics; Artificial intelligence; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003386901,0.0003210301,0.0004213146,0.0001789744,0.0004524888,0.000155497,0.0001083128,0.0001427552,0.000005416583],"category_scores_gemma":[0.000003668545,0.0002691193,0.00007330411,0.0005424279,0.00004395919,0.0002204086,3.554839e-7,0.0003426929,0.00002266678],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002398499,"about_ca_system_score_gemma":0.0001274651,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001247429,"about_ca_topic_score_gemma":0.0001433614,"domain_scores_codex":[0.998369,0.00003495812,0.000294622,0.0003903279,0.0002838264,0.0006272306],"domain_scores_gemma":[0.9993187,0.0001880655,0.00006163287,0.000198403,0.0001121972,0.0001210146],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002284075,0.00003346178,0.000001940321,0.0001844577,0.0002378927,0.000002703765,0.000710674,0.7751042,0.2213614,0.0001051269,0.0001922052,0.001837506],"study_design_scores_gemma":[0.006059957,0.003629745,0.00001903656,0.001693152,0.0002659448,0.0001281382,0.007987538,0.2259706,0.7478375,0.00007427765,0.004755546,0.001578571],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2403043,0.001121496,0.7567227,0.00004443232,0.0005311667,0.0007559642,0.00003539748,0.0003622479,0.0001222344],"genre_scores_gemma":[0.9982119,0.0002246729,0.0002764413,0.0000113619,0.0001261916,0.0002952816,0.000006553106,0.00008565139,0.0007619322],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7579076,"threshold_uncertainty_score":0.9999761,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01267514688937792,"score_gpt":0.221358710440401,"score_spread":0.208683563551023,"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."}}