{"id":"W4386078184","doi":"10.1109/tgrs.2023.3307342","title":"Efficient Rotating Synthetic Aperture Radar Imaging via Robust Sparse Array Synthesis","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Geoscience and Remote Sensing","topic":"Advanced SAR Imaging Techniques","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Synthetic aperture radar; Computer science; Robustness (evolution); Computational complexity theory; Radar imaging; Sparse array; Algorithm; Inverse synthetic aperture radar; Azimuth; Computer vision; Artificial intelligence; Radar; Mathematics","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":[0.0002923448,0.000243966,0.0002036823,0.0003629317,0.000526426,0.00008368069,0.000121053,0.00005839654,0.000004237714],"category_scores_gemma":[0.00003938435,0.0002348854,0.0000739583,0.000785396,0.0002016247,0.0001227276,0.000002515569,0.0003284092,0.00003339722],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007170488,"about_ca_system_score_gemma":0.00001530435,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005343456,"about_ca_topic_score_gemma":0.0000109858,"domain_scores_codex":[0.9985608,0.00003720064,0.0002245755,0.0004137132,0.0002678509,0.0004958917],"domain_scores_gemma":[0.9991769,0.0003338156,0.00003550995,0.0003073733,0.0000356338,0.0001108286],"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":[0.000002948835,0.000005965695,3.812147e-7,0.00003120022,0.000006250522,0.00003082537,0.0003056942,0.1638051,0.1171241,6.638356e-7,0.00001231723,0.7186745],"study_design_scores_gemma":[0.0000574641,0.000007601363,0.00001973685,0.0003036609,0.00002037204,0.0001428273,0.0002087544,0.9132881,0.08543335,0.00009249873,0.0001635372,0.0002620599],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02898173,0.00005309572,0.9680242,0.0003186761,0.000478921,0.0001624379,0.000007658985,0.001713072,0.0002601824],"genre_scores_gemma":[0.7030838,0.00008350167,0.2966177,0.00008490474,0.00002721385,6.855895e-7,4.715455e-7,0.00005131249,0.00005036216],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.749483,"threshold_uncertainty_score":0.9578347,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01184792088198126,"score_gpt":0.2226152270501923,"score_spread":0.2107673061682111,"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."}}