{"id":"W2243578182","doi":"10.1109/jstars.2015.2483758","title":"Phased-Array Beam-Diversity With Multiple Channels for Improved SAR Imaging","year":2015,"lang":"en","type":"article","venue":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","topic":"Advanced SAR Imaging Techniques","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada","funders":"","keywords":"Beamwidth; Azimuth; Phased array; Beam steering; Synthetic aperture radar; Computer science; Beam (structure); Channel (broadcasting); Optics; Phased-array optics; Antenna (radio); Sensitivity (control systems); Electronic engineering; Physics; Telecommunications; Artificial intelligence; 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":[0.0004434283,0.0003842324,0.0003294107,0.000307286,0.0002123358,0.0004292545,0.0003869215,0.000378754,0.002069539],"category_scores_gemma":[0.0007630454,0.0001746514,0.0002529962,0.0006822655,0.0002794692,0.0008175938,0.0006556054,0.0004728265,0.0004961001],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001981409,"about_ca_system_score_gemma":0.0001945037,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001361013,"about_ca_topic_score_gemma":0.000530329,"domain_scores_codex":[0.9996883,0.0001146999,0.00001133274,0.00004976691,0.0000978515,0.00003816038],"domain_scores_gemma":[0.9994142,0.0002981884,0.00006733736,0.0001190629,0.00007904071,0.00002226683],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006367959,0.0001807493,0.003125298,0.0001745012,0.0001066944,0.0002085818,0.0003096629,0.05591769,0.5397514,0.01636307,0.002139746,0.3810859],"study_design_scores_gemma":[0.0001787284,0.001012175,0.005590709,0.00006234609,0.0001177894,0.001321896,0.0001266771,0.5195781,0.4192765,0.01990791,0.03271446,0.0001126196],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1469086,0.001011678,0.8406627,0.0004170491,0.0001109095,0.00006059437,0.0001576804,0.001013226,0.009657556],"genre_scores_gemma":[0.6162317,0.0005127759,0.3794418,0.0003022641,0.0002100765,0.00007166979,0.0001643775,0.00008520004,0.002980044],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002069539,"threshold_uncertainty_score":0.006923258,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02753897704714128,"score_gpt":0.2342406471923281,"score_spread":0.2067016701451868,"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."}}