{"id":"W2592762818","doi":"","title":"Comparison between two aperture truncation mitigation schemes","year":2006,"lang":"en","type":"article","venue":"International Symposium on Antenna Technology and Applied Electromagnetics","topic":"Electromagnetic Scattering and Analysis","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Communications Research Centre Canada","funders":"","keywords":"Aperture (computer memory); Truncation (statistics); Planar; Computer science; Polarization (electrochemistry); Lossless compression; Isotropy; Optics; Mathematics; Algorithm; Physics; Acoustics; Data compression","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":[0.00007458193,0.0002318482,0.0002577991,0.0002887954,0.0001691873,0.00007420585,0.0002580578,0.0001226525,0.00008648976],"category_scores_gemma":[0.000004541064,0.0002293713,0.00006436988,0.0003898021,0.0001490333,0.00004334476,0.00004555829,0.0003338574,0.00004532298],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004427868,"about_ca_system_score_gemma":0.00001433079,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000041251,"about_ca_topic_score_gemma":0.000004576782,"domain_scores_codex":[0.9987271,0.00001500202,0.0003405366,0.0003993683,0.0002087339,0.00030926],"domain_scores_gemma":[0.9994468,0.00007888619,0.000159806,0.0001974375,0.00007521881,0.00004182391],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001856493,0.0001246269,0.0932387,0.000003289368,0.00008674137,5.392461e-7,0.00001300251,0.00002143897,0.5427943,0.3537964,0.0001774019,0.009724967],"study_design_scores_gemma":[0.004819163,0.001715446,0.08651678,0.0001216382,0.0004794361,0.0000241067,0.0002857383,0.01545626,0.6451062,0.2101111,0.03353,0.001834206],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9671423,0.00008889379,0.006638551,0.007614074,0.00005670355,0.000144004,0.00001979998,0.0001713967,0.01812431],"genre_scores_gemma":[0.9973067,0.000009992948,0.001174345,0.0001410744,0.0003597976,0.00005208259,0.0002817211,0.00002131278,0.0006529752],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1436854,"threshold_uncertainty_score":0.935349,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00446324146583786,"score_gpt":0.2466323006117919,"score_spread":0.242169059145954,"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."}}