{"id":"W4293868584","doi":"10.1109/ims37962.2022.9865470","title":"Analytical Expressions for Field-based Response Sensitivity Analysis and Their Application in Microwave Design and Imaging","year":2022,"lang":"en","type":"article","venue":"2022 IEEE/MTT-S International Microwave Symposium - IMS 2022","topic":"Microwave Imaging and Scattering Analysis","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Sensitivity (control systems); Computer science; Microwave; Field (mathematics); Electronic engineering; Overhead (engineering); Engineering; Mathematics; Telecommunications","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":[0.001728046,0.0003645238,0.0004750806,0.001201002,0.0003178228,0.0001525768,0.0002901402,0.0000724104,0.00008359366],"category_scores_gemma":[0.00009017777,0.0004023615,0.0002700193,0.000847277,0.0000890553,0.0001428661,0.0002109718,0.0004960631,0.000002943636],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003852247,"about_ca_system_score_gemma":0.00005334501,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001698759,"about_ca_topic_score_gemma":0.0001060431,"domain_scores_codex":[0.9975587,0.0004590017,0.0005366886,0.0007512438,0.0002826019,0.0004118292],"domain_scores_gemma":[0.99797,0.001254869,0.0001243548,0.0004311065,0.00008596743,0.0001337064],"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":[0.0003630612,0.00007677112,0.004974078,0.00002822936,0.0004545167,0.00002703024,0.0005121056,0.08763602,0.9019837,0.00003182877,0.001604052,0.00230855],"study_design_scores_gemma":[0.0006731764,0.00004178691,0.001142437,0.00001885384,0.0002289519,0.0000620851,0.0004259076,0.8407668,0.1541764,0.0001715437,0.001881627,0.0004104718],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4508637,0.000279705,0.5448341,0.002899149,0.0002807491,0.0003582302,0.0002653284,0.0001105485,0.0001084873],"genre_scores_gemma":[0.9949437,0.00005779006,0.003526592,0.0005184386,0.00007588985,0.0003342344,0.0002401133,0.00006152452,0.0002417501],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7531308,"threshold_uncertainty_score":0.9998428,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007556781821252266,"score_gpt":0.2346181828280431,"score_spread":0.2270614010067908,"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."}}