{"id":"W3202596225","doi":"10.1109/aces53325.2021.00084","title":"Fast Direct Solution of 2D Scalar Volume Integral Equation via Tensor Train Decomposition for Scatterers of Arbitrary Shape","year":2021,"lang":"en","type":"article","venue":"2021 International Applied Computational Electromagnetics Society Symposium (ACES)","topic":"Electromagnetic Scattering and Analysis","field":"Physics and Astronomy","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Integral equation; Discretization; Mathematics; Tensor (intrinsic definition); Matrix (chemical analysis); Conjugate gradient method; Scalar (mathematics); Mathematical analysis; Constant (computer programming); Rank (graph theory); Applied mathematics; Geometry; Algorithm; Computer science","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":[0.0002538603,0.0003042562,0.0004568513,0.0001275707,0.0001562703,0.00007342619,0.0003194678,0.0001099778,0.0006358171],"category_scores_gemma":[0.000008797973,0.0003510654,0.000625495,0.0004507019,0.0001439854,0.0001232457,0.00007440627,0.0002212654,0.00001003717],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001261338,"about_ca_system_score_gemma":0.0002594892,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006256479,"about_ca_topic_score_gemma":0.000003492261,"domain_scores_codex":[0.9976004,0.00006441223,0.0007913308,0.0005568406,0.0006195718,0.0003674332],"domain_scores_gemma":[0.9981515,0.0002682248,0.0004896151,0.0001969545,0.0008065272,0.00008712895],"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":[0.0001350039,0.0008316432,0.002005292,0.0001018633,0.001207155,7.385195e-7,0.0006942654,0.03918291,0.9141449,0.02204413,0.001717508,0.01793461],"study_design_scores_gemma":[0.001856215,0.0004852822,0.002992665,0.00007881912,0.0003874141,0.00001000521,0.00044581,0.8702261,0.09802492,0.02474082,0.0002448169,0.0005070955],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4259014,0.0001489241,0.563071,0.003346632,0.0002550642,0.0004683816,0.0003988887,0.00004606131,0.00636372],"genre_scores_gemma":[0.9352499,0.00001731398,0.06051457,0.0001621791,0.0003485986,0.0001166396,0.003089646,0.00003836559,0.0004628083],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8310432,"threshold_uncertainty_score":0.9998941,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005989203296588238,"score_gpt":0.2340038599638918,"score_spread":0.2280146566673035,"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."}}