{"id":"W3045533511","doi":"10.1080/09205071.2020.1791258","title":"Sub-structure characteristic mode computation utilising field-based MM/GTD hybrid methods","year":2020,"lang":"en","type":"article","venue":"Journal of Electromagnetic Waves and Applications","topic":"Electromagnetic Scattering and Analysis","field":"Physics and Astronomy","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computation; Scope (computer science); Mode (computer interface); Realisation; Diffraction; Object (grammar); Field (mathematics); Method of moments (probability theory); Computer science; Uniform theory of diffraction; Algorithm; Optics; Mathematics; Physics; Pure mathematics; Artificial intelligence; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003432439,0.000430716,0.0004275385,0.0005819064,0.0001905715,0.000707493,0.0007227961,0.0008672969,0.002541238],"category_scores_gemma":[0.0007545879,0.0002387385,0.0004663532,0.000437869,0.0004632681,0.0007017349,0.0008100152,0.0005205292,0.0006272951],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003291423,"about_ca_system_score_gemma":0.0003605337,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007831636,"about_ca_topic_score_gemma":0.001064279,"domain_scores_codex":[0.9998831,0.00003200246,0.000004846888,0.00001063083,0.00005553718,0.00001389365],"domain_scores_gemma":[0.9996508,0.0001722529,0.00002661349,0.00006182891,0.00006615862,0.00002232488],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003164276,0.0001012383,0.002211879,0.0003372204,0.00008698172,0.0002696834,0.0003233688,0.6467985,0.07430254,0.121173,0.002023468,0.1520557],"study_design_scores_gemma":[0.00001078601,0.00001911836,0.000125791,0.000007458193,0.000002805879,0.00005424655,0.00002020036,0.9886937,0.00280804,0.0067566,0.00149391,0.00000736137],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01903179,0.0001023156,0.9766932,0.00006281839,0.00003133856,0.00002258257,0.00002985782,0.0002720644,0.003754107],"genre_scores_gemma":[0.3857671,0.0001451311,0.6097625,0.00006735951,0.00002444034,0.00008127533,0.00008539356,0.0001477335,0.003919039],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002541238,"threshold_uncertainty_score":0.008501291,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008373092444218503,"score_gpt":0.2858568089018104,"score_spread":0.2774837164575919,"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."}}