{"id":"W4392981035","doi":"10.1109/mapcon58678.2023.10464012","title":"Cross-correlated Tensor Surface Impedance Characterization of Orthogonally Discrete IMU & CMU for Impedance Modulated Metasurface","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Antenna and Metasurface Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Military College of Canada","funders":"","keywords":"Electrical impedance; Characterization (materials science); Tensor (intrinsic definition); Physics; Surface (topology); Inertial measurement unit; Computer science; Optics; Mathematics; Artificial intelligence; Geometry; Quantum mechanics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003239225,0.0003670288,0.0005616251,0.0001327516,0.0001055285,0.00003834161,0.0003442994,0.0002366897,0.00003654052],"category_scores_gemma":[0.0002529976,0.0003303272,0.0001899419,0.001073443,0.000136609,0.000449735,0.00007813354,0.000211259,0.00009483308],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004477333,"about_ca_system_score_gemma":0.000025276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008444821,"about_ca_topic_score_gemma":0.00001229456,"domain_scores_codex":[0.9980506,0.00001997084,0.0006408901,0.0004255079,0.0002430578,0.0006199731],"domain_scores_gemma":[0.9987661,0.0001463433,0.0001738169,0.0005498036,0.0002887509,0.0000752433],"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":[0.00004112882,0.000009747043,0.002202733,0.0001310672,0.00009586632,0.000001701145,0.00007203153,0.2083076,0.787386,0.0002202467,0.00005148,0.001480382],"study_design_scores_gemma":[0.001130059,0.00008506222,0.04203692,0.0001128781,0.00007330877,0.000006645502,0.00009787962,0.5296522,0.4200478,0.0007304116,0.005226559,0.0008003046],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8780698,0.0002679046,0.1169968,0.00008100883,0.0004305912,0.0005957561,0.0003669322,0.003096448,0.00009477112],"genre_scores_gemma":[0.9803838,0.0008013625,0.01355426,0.00001493041,0.00001695,0.00004624811,0.0003899584,0.0001120248,0.004680438],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3673382,"threshold_uncertainty_score":0.9999149,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02200901969273872,"score_gpt":0.2870024367597032,"score_spread":0.2649934170669644,"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."}}