{"id":"W2206422526","doi":"","title":"Optimum GMTI Processing for Space-based SAR/GMTI Systems - Simulation Results","year":2010,"lang":"en","type":"article","venue":"Synthetic Aperture Radar (EUSAR), 2010 8th European Conference on","topic":"Advanced SAR Imaging Techniques","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Moving target indication; Computer science; Synthetic aperture radar; Phase center; Computer vision; Artificial intelligence; Remote sensing; Antenna (radio); Radar; Radar imaging; Geography; Telecommunications; Continuous-wave radar","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":[0.0005640166,0.0002972783,0.0003580671,0.0002557456,0.0001744179,0.0003850163,0.0002122188,0.0005188101,0.00146656],"category_scores_gemma":[0.002171698,0.0001721113,0.0003107242,0.0003967471,0.0002708417,0.0005049793,0.0002348793,0.0003280018,0.0002800983],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003005393,"about_ca_system_score_gemma":0.0003339222,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002622446,"about_ca_topic_score_gemma":0.002332621,"domain_scores_codex":[0.99972,0.00009202142,0.00001080402,0.00002444987,0.0001047458,0.00004790641],"domain_scores_gemma":[0.9990789,0.0006284801,0.00006868958,0.00004835433,0.0001571965,0.00001836594],"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":[0.0001423953,0.00001377005,0.0007420955,0.00004883756,0.00001636485,0.00005037802,0.00005611351,0.9850746,0.005096795,0.001908174,0.0002874495,0.006562972],"study_design_scores_gemma":[0.00001237041,0.00003501869,0.0003044823,0.000003750854,0.000005599971,0.00002702171,0.00001397207,0.9951059,0.003677308,0.0005778433,0.0002321565,0.000004626936],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5145909,0.00054617,0.4673083,0.0004159987,0.00003111074,0.00007783178,0.0002523897,0.0006071922,0.01617003],"genre_scores_gemma":[0.9681318,0.0001015194,0.0306891,0.00002715162,0.000007527527,0.00002422206,0.0001003316,0.000043714,0.0008745944],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002622446,"threshold_uncertainty_score":0.005214334,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02555512048929132,"score_gpt":0.262381412375174,"score_spread":0.2368262918858827,"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."}}