{"id":"W2165150416","doi":"10.1109/ciss.2006.286686","title":"Space-Time-Waveform Adaptive Processing for Frequency Diverse Distributed Radar Apertures","year":2006,"lang":"en","type":"article","venue":"","topic":"Radar Systems and Signal Processing","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Radar; Computer science; Continuous-wave radar; Waveform; Space-time adaptive processing; Radar engineering details; Remote sensing; Synthetic aperture radar; Radar imaging; Diversity scheme; Fire-control radar; Space-based radar; Telecommunications; Geology; Computer vision; Fading","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":[0.0001004043,0.0002271943,0.0002489257,0.00006532241,0.0002078919,0.00010901,0.0001220409,0.000110975,0.00004617697],"category_scores_gemma":[0.00001503701,0.000184446,0.00009017502,0.0001803631,0.00003385293,0.0003585215,0.00001451526,0.0001001229,0.00002050107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001230819,"about_ca_system_score_gemma":0.00003485251,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001843106,"about_ca_topic_score_gemma":0.00004836101,"domain_scores_codex":[0.998966,0.000007677976,0.0002725689,0.0002088375,0.0001768577,0.0003680256],"domain_scores_gemma":[0.9996282,0.00004502614,0.00005042669,0.000118436,0.00009011827,0.00006776829],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003252305,0.0004715951,0.001633884,0.004585124,0.0006485127,0.0001833193,0.002715701,0.1044455,0.4343775,0.04096235,0.2728342,0.1368171],"study_design_scores_gemma":[0.002146709,0.0001987856,0.001045782,0.0004415618,0.0001218683,0.0000507974,0.001079227,0.9146339,0.0330515,0.01145913,0.03412772,0.001642978],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02844919,0.002807678,0.9031293,0.0001618418,0.0003648298,0.0008034366,0.0002181717,0.001425984,0.06263958],"genre_scores_gemma":[0.983475,0.000002749975,0.01470171,0.00002289121,0.0003579722,0.00002937756,0.00008529414,0.00004984568,0.001275116],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9550259,"threshold_uncertainty_score":0.7521489,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009650267369238047,"score_gpt":0.195795639453437,"score_spread":0.186145372084199,"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."}}