{"id":"W2151387183","doi":"10.1109/igarss.1993.322128","title":"An approach for improved processing in squint mode SAR","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced SAR Imaging Techniques","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Range (aeronautics); Operator (biology); Computer science; Synthetic aperture radar; Chirp; Algorithm; Signal processing; Phase (matter); Modulation (music); Artificial intelligence; Computer vision; Radar; Optics; Physics; Telecommunications; Acoustics","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":[0.000454307,0.000733884,0.0002623336,0.0004043992,0.0003693482,0.0007414843,0.0008015415,0.0006983465,0.006018373],"category_scores_gemma":[0.001079057,0.0002515883,0.0004250276,0.0004742845,0.0004635453,0.001457592,0.001256224,0.00105135,0.001656715],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002715486,"about_ca_system_score_gemma":0.0004067929,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004894258,"about_ca_topic_score_gemma":0.001005636,"domain_scores_codex":[0.999663,0.00005559368,0.00001636955,0.00006431451,0.0001793753,0.00002141382],"domain_scores_gemma":[0.9996613,0.00005797724,0.0000227345,0.000105053,0.0001349902,0.00001790292],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002909763,0.0001487671,0.0006333148,0.0002301015,0.00005089993,0.000269606,0.0003061741,0.03012107,0.337605,0.1331088,0.007696655,0.4895386],"study_design_scores_gemma":[0.0000638735,0.0006102748,0.00202442,0.00007547708,0.00006137736,0.001515081,0.0001183199,0.5932096,0.1826808,0.08581935,0.1337214,0.0001000693],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005791943,0.000219534,0.9867375,0.0002668585,0.0001115066,0.00004358265,0.0000419864,0.0007431465,0.00604388],"genre_scores_gemma":[0.05265342,0.0003416269,0.9368773,0.0002316799,0.0001399427,0.00006672534,0.0001456976,0.0001544484,0.009389061],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006018373,"threshold_uncertainty_score":0.02013344,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01917789875940526,"score_gpt":0.27065301162563,"score_spread":0.2514751128662248,"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."}}