{"id":"W2075804008","doi":"10.1109/spi.2010.5483584","title":"A novel broadband boundary element approach for RL-extraction in lossy 3D interconnects","year":2010,"lang":"en","type":"article","venue":"","topic":"Electromagnetic Scattering and Analysis","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"","keywords":"Inductance; Boundary element method; Integral equation; Lossy compression; Exponential function; Mathematical analysis; Broadband; Attenuation; Boundary value problem; Boundary (topology); Current density; Skin effect; Electronic engineering; Acoustics; Computer science; Finite element method; Mathematics; Physics; Engineering; Optics; Electrical engineering; Telecommunications; Structural engineering; Voltage","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":[0.0002964691,0.0005398075,0.0005082791,0.0004997022,0.0003186119,0.0006802723,0.000771681,0.0008769355,0.002399617],"category_scores_gemma":[0.0007371289,0.000433461,0.0004733602,0.0003152875,0.0003696383,0.0009675246,0.0007624381,0.0006214671,0.001590547],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003532865,"about_ca_system_score_gemma":0.0003354905,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004851764,"about_ca_topic_score_gemma":0.0008083797,"domain_scores_codex":[0.9998181,0.00004509138,0.000008080369,0.00001937411,0.00009693849,0.0000123825],"domain_scores_gemma":[0.9997935,0.00009766945,0.00001944164,0.00002971926,0.00005134219,0.000008350386],"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":[0.00007052007,0.00007093503,0.000388714,0.0003783669,0.00004793168,0.0002365593,0.0003900705,0.5274955,0.2194413,0.08598587,0.002897962,0.1625963],"study_design_scores_gemma":[0.000006827383,0.00002218412,0.00008378566,0.00002802317,0.00000644198,0.00009775266,0.00002230532,0.9651492,0.01631876,0.009665492,0.008582244,0.00001697945],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001577009,0.00003934429,0.9969019,0.0000257492,0.00000647571,0.000007877838,0.00001605395,0.0002329176,0.001192732],"genre_scores_gemma":[0.09846354,0.0002112447,0.8971962,0.0000809409,0.00002058491,0.0001408269,0.0001378086,0.0002353001,0.003513574],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002399617,"threshold_uncertainty_score":0.008027554,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008842593840191327,"score_gpt":0.2553509610635756,"score_spread":0.2465083672233843,"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."}}