{"id":"W2996807102","doi":"10.2514/6.2020-1455","title":"Air Sanitization Using AESA Radar","year":2020,"lang":"en","type":"article","venue":"AIAA Scitech 2020 Forum","topic":"Target Tracking and Data Fusion in Sensor Networks","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lockheed Martin (Canada)","funders":"","keywords":"Synthetic aperture radar; Computer science; Boundary (topology); Radar tracker; Radar; Aperture (computer memory); Tracking (education); Remote sensing; Computer vision; Telecommunications; Acoustics; Geology; Physics; Mathematics","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":[0.000133798,0.0001699632,0.0001744915,0.00005561599,0.0002914769,0.0001847859,0.000912239,0.0001005142,0.00005455893],"category_scores_gemma":[0.0000759505,0.0001677488,0.00007508013,0.001016281,0.00004349451,0.0005274812,0.0004806244,0.0002267154,0.0001622707],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002908531,"about_ca_system_score_gemma":0.00005642286,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002439483,"about_ca_topic_score_gemma":0.000003898832,"domain_scores_codex":[0.9983599,0.00005575582,0.0002713801,0.0005262558,0.0003682493,0.0004184664],"domain_scores_gemma":[0.9990821,0.00005740705,0.0001018846,0.0004734463,0.00007777812,0.0002073502],"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":[0.00008924367,0.0002255454,0.006599521,0.0001344804,0.000114741,0.0004908449,0.002969867,0.02675192,0.05758662,0.1676844,0.4413024,0.2960504],"study_design_scores_gemma":[0.0005962859,0.0001636543,0.0003860885,0.00006510945,0.00001603832,0.0000649923,0.0001668928,0.7099646,0.008911655,0.003911262,0.2751497,0.0006037639],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006489264,0.0002010278,0.9768298,0.01370147,0.0007660986,0.0001619526,0.00001783162,0.0007094624,0.001123133],"genre_scores_gemma":[0.8166884,0.00003908028,0.1737552,0.008968288,0.0004173512,0.000003928629,0.00003856706,0.00002748509,0.00006165195],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8101991,"threshold_uncertainty_score":0.6840598,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02088827568471755,"score_gpt":0.2348855788809671,"score_spread":0.2139973031962495,"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."}}