{"id":"W4386523584","doi":"10.1109/usnc-ursi52151.2023.10237683","title":"UAV Classification Utilizing Radar Digital Twins","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Optical Sensing Technologies","field":"Physics and Astronomy","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Radar; Computer science; Identification (biology); CAD; Secondary surveillance radar; Radar engineering details; Radar configurations and types; Real-time computing; Radar lock-on; Radar tracker; Radar imaging; Artificial intelligence; Remote sensing; Engineering; Telecommunications; Geography","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00002128861,0.00006412154,0.00006456975,0.00003767051,0.00006114548,0.0000507953,0.00008495079,0.00002225056,0.0000559408],"category_scores_gemma":[0.00002031458,0.00005491226,0.00003377443,0.0002517516,0.00005175576,0.0001527419,0.00007002346,0.00007418864,0.0006594898],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001104543,"about_ca_system_score_gemma":0.000006780172,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004949917,"about_ca_topic_score_gemma":2.56091e-7,"domain_scores_codex":[0.9995296,0.000002513364,0.00008811569,0.0001407485,0.00006985894,0.0001691783],"domain_scores_gemma":[0.999705,0.00005255898,0.00002174726,0.0001789676,0.00001753355,0.00002422485],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000001950017,0.00002307551,0.009297145,0.000001306254,0.00001283182,0.00000113897,0.00002083748,0.00001811747,0.004001255,0.7101084,0.002010395,0.2745036],"study_design_scores_gemma":[0.0006595508,0.00007280563,0.04343731,0.00003426767,0.00002024627,0.000001186363,0.008990579,0.02404342,0.03516555,0.7500883,0.1367211,0.0007656145],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5306301,0.000005456309,0.1168966,0.002228363,0.0001569578,0.0001675581,0.00002001096,0.002705551,0.3471893],"genre_scores_gemma":[0.99315,6.118066e-7,0.005211327,0.00001222736,0.00004808037,0.000003092764,0.00003233461,0.000009618318,0.001532707],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4625199,"threshold_uncertainty_score":0.8476627,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03935868737232003,"score_gpt":0.2850781243694021,"score_spread":0.245719436997082,"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."}}