{"id":"W4402263690","doi":"10.1109/igarss53475.2024.10640501","title":"Gaussian Process Regression for Empirical Radar Cross Section Modeling Based on the SCATR ISAR Dataset","year":2024,"lang":"en","type":"article","venue":"","topic":"Risk and Safety Analysis","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Department of National Defence","funders":"U.S. Naval Research Laboratory","keywords":"Radar cross-section; Inverse synthetic aperture radar; Gaussian process; Computer science; Radar; Process (computing); Gaussian; Radar imaging; Telecommunications; Physics","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":[0.003427198,0.0001515247,0.0002006687,0.0002372077,0.0006147062,0.000859753,0.0006185527,0.0001399753,0.0006158452],"category_scores_gemma":[0.00091702,0.00006518929,0.0002207838,0.00114412,0.00006660788,0.0003855808,0.00004722918,0.000265859,0.0002039565],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003594153,"about_ca_system_score_gemma":0.0001340455,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003481408,"about_ca_topic_score_gemma":0.00005350553,"domain_scores_codex":[0.9972627,0.0001587531,0.0004879873,0.0006702258,0.001188968,0.0002313535],"domain_scores_gemma":[0.9974768,0.001497802,0.0000666907,0.0007122474,0.0001581882,0.0000882618],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006333858,0.0001719359,0.001388361,0.00005445159,0.00006371907,0.00001506605,0.0009465297,0.3398258,0.0001702294,0.002433182,0.5943429,0.05995439],"study_design_scores_gemma":[0.0001239664,0.00004550649,0.00005798572,0.00003809615,0.00002393155,0.000001734398,0.0004734217,0.9227615,0.0003603302,0.01510359,0.06090541,0.0001045049],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08025599,0.0002273896,0.8468122,0.06634369,0.0009234119,0.0005482876,0.001133101,0.0001887447,0.003567179],"genre_scores_gemma":[0.9945927,0.00001695542,0.001467939,0.001500804,0.0002967569,0.00003438339,0.0002884966,0.00001503761,0.001786876],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9143367,"threshold_uncertainty_score":0.8290618,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2078177065889973,"score_gpt":0.4927660815918059,"score_spread":0.2849483750028087,"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."}}