{"id":"W2132013194","doi":"10.1109/aps.1996.549934","title":"Power pattern error compensation method for SAR phased-array application","year":2002,"lang":"en","type":"article","venue":"","topic":"Antenna Design and Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Phased array; Compensation (psychology); Antenna (radio); Phased-array optics; Computer science; Synthetic aperture radar; Phase compensation; Electronic engineering; Engineering; Telecommunications; Artificial intelligence; Phase noise","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008087063,0.00008510301,0.00008390532,0.00004643204,0.00003795085,0.00001831705,0.00005409299,0.00005518021,0.0005825647],"category_scores_gemma":[0.000006591053,0.00008185372,0.00003625708,0.00007988334,0.00000552532,0.0001004107,0.000001284393,0.0000358755,0.0001085424],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002741552,"about_ca_system_score_gemma":0.000001087126,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004170312,"about_ca_topic_score_gemma":0.000003065274,"domain_scores_codex":[0.9995608,0.00001092748,0.000135367,0.0001129231,0.00006333667,0.000116613],"domain_scores_gemma":[0.9997487,0.00003780948,0.00002022602,0.0001191444,0.00004152031,0.00003260419],"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":[0.00002161081,0.0001807944,0.0003609193,0.0001432759,0.0001004365,4.878016e-7,0.001485065,0.0974298,0.7004445,0.003388257,0.03278988,0.163655],"study_design_scores_gemma":[0.0003182549,0.00002126515,0.00006662012,0.000003465642,0.000008256181,0.000001279205,0.00003764232,0.9676164,0.01306275,0.00008126983,0.01866473,0.0001181113],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0001772482,0.00005577632,0.9890201,0.0001932516,0.00008975944,0.000344508,0.000006306939,0.0003044891,0.009808559],"genre_scores_gemma":[0.819546,0.00001210252,0.1794715,0.0002657383,0.00004968825,0.00004399127,0.0000411015,0.00002979097,0.0005400662],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8701866,"threshold_uncertainty_score":0.6378675,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02197028857293071,"score_gpt":0.2572222125327241,"score_spread":0.2352519239597934,"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."}}