{"id":"W2088799819","doi":"10.1109/aero.2010.5446687","title":"Multitarget track before detect with MIMO radars","year":2010,"lang":"en","type":"article","venue":"","topic":"Radar Systems and Signal Processing","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"MIMO; Computer science; Radar tracker; Bistatic radar; Multistatic radar; Low probability of intercept radar; Radar; Radar engineering details; Algorithm; Passive radar; Electronic engineering; Channel (broadcasting); Telecommunications; Engineering; Radar imaging","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":[0.00006978022,0.0001102957,0.0001127622,0.00003457426,0.00004967639,0.00004247858,0.00008521289,0.00006449062,0.0001384462],"category_scores_gemma":[0.000005158806,0.00007614916,0.00002628392,0.00008000099,0.0000195877,0.0001398481,0.000004584047,0.0001960487,0.00004234871],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008319017,"about_ca_system_score_gemma":0.00001084756,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000449563,"about_ca_topic_score_gemma":0.0007887884,"domain_scores_codex":[0.9994917,0.000003314211,0.000114305,0.0001042039,0.0001085336,0.0001779232],"domain_scores_gemma":[0.9997575,0.00001019476,0.00001180282,0.0001306538,0.00002096308,0.00006892347],"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":[0.0000594899,0.0001076245,0.009369312,0.001009992,0.0003182551,0.0002034159,0.003021872,0.01922664,0.6462095,0.001711581,0.01790434,0.300858],"study_design_scores_gemma":[0.003012497,0.0005750363,0.01622755,0.0002323323,0.00007059109,0.0004800026,0.0008286412,0.4303088,0.3084197,0.0006699646,0.2372161,0.001958827],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9500596,0.0001240488,0.02472129,0.00002885057,0.0003564918,0.0001069673,0.000002329668,0.0004706482,0.02412975],"genre_scores_gemma":[0.9804466,7.879345e-7,0.01876465,0.00001736126,0.0001210297,0.000004122538,0.000001323186,0.00003206775,0.0006120704],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4110821,"threshold_uncertainty_score":0.3105273,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003777576579030527,"score_gpt":0.1804655911004694,"score_spread":0.1766880145214389,"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."}}