{"id":"W2493730065","doi":"10.1109/lgrs.2016.2566660","title":"An Improved Oblique Projection Method for Sea Clutter Suppression in Shipborne HFSWR","year":2016,"lang":"en","type":"article","venue":"IEEE Geoscience and Remote Sensing Letters","topic":"Radar Systems and Signal Processing","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Clutter; Doppler effect; Oblique projection; Azimuth; Doppler radar; Weighting; Geology; Radar; Projection (relational algebra); Remote sensing; Frequency domain; Radar horizon; Acoustics; Computer science; Orthographic projection; Continuous-wave radar; Radar imaging; Optics; Physics; Artificial intelligence; Telecommunications; Algorithm; Computer vision","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003729211,0.000658202,0.0004346231,0.0003551478,0.0002360732,0.0004663197,0.0004195517,0.0003593796,0.001001459],"category_scores_gemma":[0.0007516003,0.0002060479,0.0004057937,0.0007603742,0.0003535286,0.0007532753,0.0006611569,0.0005943601,0.0004051056],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001085707,"about_ca_system_score_gemma":0.000601052,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001205179,"about_ca_topic_score_gemma":0.001008571,"domain_scores_codex":[0.9996636,0.00006968227,0.00001760769,0.00004035228,0.0001778434,0.00003091625],"domain_scores_gemma":[0.9997806,0.00005744662,0.00002636072,0.00002948555,0.00008949837,0.00001667185],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002261433,0.00009611119,0.001756676,0.0001966276,0.00006787005,0.0002345943,0.0002116759,0.06441732,0.1589021,0.01091888,0.001686716,0.7612853],"study_design_scores_gemma":[0.00003374893,0.0001617142,0.001573049,0.00001855599,0.00003777085,0.0005398048,0.00005907134,0.9389334,0.04973658,0.002554983,0.006309759,0.00004168669],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01538012,0.0001977998,0.9835545,0.0000275461,0.00002743873,0.000017642,0.00001299951,0.0001259053,0.0006559691],"genre_scores_gemma":[0.1802021,0.0009011359,0.8162087,0.00006392488,0.00007495695,0.00006726574,0.0001380862,0.00008520484,0.002258776],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001205179,"threshold_uncertainty_score":0.003350198,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01111833099111371,"score_gpt":0.2559198192136455,"score_spread":0.2448014882225318,"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."}}