{"id":"W2102533265","doi":"10.1109/radar.2005.1435800","title":"Waveform-space-time adaptive processing for distributed aperture radars","year":2005,"lang":"en","type":"article","venue":"","topic":"Radar Systems and Signal Processing","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Waveform; Computer science; Synthetic aperture radar; Space-time adaptive processing; Remote sensing; Real-time computing; Electronic engineering; Radar; Radar imaging; Radar engineering details; Telecommunications; Geology; Computer vision; Engineering","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":[0.0005222433,0.000415129,0.0003189548,0.0002302157,0.000200306,0.0004773517,0.0005435585,0.0005362861,0.001447088],"category_scores_gemma":[0.001596135,0.0001801391,0.000323311,0.000505202,0.0003644116,0.0009408559,0.0003961405,0.001003721,0.0008379818],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002401567,"about_ca_system_score_gemma":0.0002726179,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004555966,"about_ca_topic_score_gemma":0.0006311908,"domain_scores_codex":[0.9997303,0.00007785371,0.00001450036,0.00005126992,0.0001114648,0.00001465657],"domain_scores_gemma":[0.9994892,0.0002344155,0.00003751213,0.00008034781,0.0001401966,0.00001830393],"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":[0.0001043571,0.00007067651,0.00048016,0.0001741991,0.00004485563,0.0001147352,0.0001143347,0.4235998,0.04174297,0.2105936,0.003166037,0.3197943],"study_design_scores_gemma":[0.000005918676,0.00003041458,0.000054562,0.000005405575,0.000003575304,0.00003957329,0.000006442793,0.9751714,0.002699344,0.01897983,0.002997096,0.000006421189],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00120723,0.00009682462,0.9980733,0.0000573975,0.00002065661,0.000006049138,0.00001027307,0.00005100499,0.0004772602],"genre_scores_gemma":[0.2070432,0.001620852,0.7856007,0.0002009245,0.0002437913,0.0001117813,0.000230518,0.00008887743,0.004859465],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001447088,"threshold_uncertainty_score":0.00484097,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007944629850799901,"score_gpt":0.1974521890703257,"score_spread":0.1895075592195258,"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."}}