{"id":"W4300466799","doi":"","title":"Preconditioning of a Low-Frequency Electric Field Integral Equation Formulation with Circuit Coupling using H-matrices","year":2016,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Electromagnetic Scattering and Analysis","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Center for Diagnosis and Research on Alzheimer's Disease","funders":"","keywords":"Electric-field integral equation; Coupling (piping); Integral equation; Electric field; Field (mathematics); Physics; Electrical engineering; Quantum electrodynamics; Materials science; Mathematical analysis; Mathematics; Engineering; 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":[0.0004083684,0.0006009706,0.0005914532,0.00023991,0.0003196232,0.0008753901,0.0007068245,0.0008407355,0.01020044],"category_scores_gemma":[0.001192664,0.0002205801,0.0003850993,0.0003325516,0.0006947063,0.0008623226,0.0009135769,0.001144637,0.001369624],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000311918,"about_ca_system_score_gemma":0.0006774628,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001693142,"about_ca_topic_score_gemma":0.002502743,"domain_scores_codex":[0.9997584,0.00009556514,0.00001168432,0.00003027215,0.000075845,0.00002826102],"domain_scores_gemma":[0.9994649,0.0002436979,0.00004426537,0.00007867711,0.0001134396,0.00005491028],"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":[0.0003516568,0.0003639071,0.0007356391,0.0004115031,0.00006921622,0.0006224994,0.0003914536,0.6044481,0.06276417,0.1983645,0.01009584,0.1213815],"study_design_scores_gemma":[0.00002327876,0.00004275923,0.00009170298,0.000008267386,0.000005638459,0.00003218366,0.00003341567,0.9791188,0.00486961,0.01230321,0.003463574,0.000007635537],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0258107,0.00008460249,0.9603742,0.0002898992,0.0001609561,0.00004662308,0.00007237609,0.0003275409,0.01283317],"genre_scores_gemma":[0.49033,0.0002669492,0.4812822,0.0003604324,0.0002037292,0.0001441048,0.0003029887,0.0006182422,0.02649137],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01020044,"threshold_uncertainty_score":0.0341239,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01048933024994774,"score_gpt":0.2132511647528684,"score_spread":0.2027618345029206,"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."}}