{"id":"W2131476315","doi":"10.1109/taes.2011.5937266","title":"Detection Performance using Frequency Diversity with Distributed Sensors","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Aerospace and Electronic Systems","topic":"Radar Systems and Signal Processing","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Antenna diversity; Diversity scheme; Interference (communication); Computer science; Space-time adaptive processing; Context (archaeology); Radar; Diversity combining; Signal-to-noise ratio (imaging); Diversity gain; Electronic engineering; Radar engineering details; Telecommunications; Radar imaging; Fading; Engineering; Geography","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001217963,0.0006208186,0.0005985858,0.0003922908,0.000371051,0.0007528989,0.0004964912,0.001141709,0.0003991907],"category_scores_gemma":[0.006064264,0.0002441062,0.0003281166,0.000459767,0.0005852397,0.001273817,0.0008238555,0.0004654777,0.000145303],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006039421,"about_ca_system_score_gemma":0.0005483297,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001161893,"about_ca_topic_score_gemma":0.000855024,"domain_scores_codex":[0.9990895,0.000280139,0.0000219645,0.0001914261,0.0003088199,0.0001082378],"domain_scores_gemma":[0.9954726,0.003294237,0.0003331429,0.0002715488,0.000555499,0.00007297313],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001022525,0.0001931606,0.006360187,0.0001670834,0.0001537595,0.000378082,0.0001915893,0.8457257,0.05276537,0.01018434,0.0005177289,0.08234052],"study_design_scores_gemma":[0.000034234,0.0002885766,0.0007399262,0.00000745555,0.00002291002,0.0001943504,0.00002855901,0.9872165,0.008629953,0.002597331,0.0002208909,0.0000193104],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5379757,0.0009924195,0.4533242,0.0003915967,0.00006975292,0.00003450663,0.00005093402,0.0002835564,0.006877392],"genre_scores_gemma":[0.9855258,0.0001333106,0.0136906,0.0000359502,0.00001763731,0.00001031616,0.0000179313,0.0000054228,0.0005631571],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001217963,"threshold_uncertainty_score":0.006441295,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01537665519055374,"score_gpt":0.1740500314109947,"score_spread":0.1586733762204409,"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."}}