{"id":"W2156662737","doi":"10.1109/tcad.2010.2090065","title":"Transient Simulation of Distributed Networks Using Delay Extraction Based Numerical Convolution","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems","topic":"Lightning and Electromagnetic Phenomena","field":"Physics and Astronomy","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Convolution (computer science); Transient (computer programming); Frequency domain; Computer science; Algorithm; Time domain; Nonlinear system; Fourier transform; Fast Fourier transform; Overlap–add method; Piecewise linear function; Piecewise; Computer simulation; Inverse; Mathematics; Mathematical analysis; Fourier analysis; Simulation; Geometry; Physics; Artificial intelligence","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":[],"consensus_categories":[],"category_scores_codex":[0.0002362808,0.0002245659,0.0004003409,0.000164062,0.0001282263,0.00002717512,0.00008964982,0.0001004348,0.00004100735],"category_scores_gemma":[9.839199e-7,0.000199991,0.0001081936,0.0003410405,0.00006283102,0.0001263775,5.227478e-7,0.0002106494,9.090933e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006274457,"about_ca_system_score_gemma":0.0000856461,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007750258,"about_ca_topic_score_gemma":5.96041e-7,"domain_scores_codex":[0.9984405,0.0002524746,0.0006137421,0.0002775499,0.0001793296,0.0002363849],"domain_scores_gemma":[0.9989823,0.0001947048,0.0002945777,0.0001860281,0.0002467084,0.00009569333],"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":[0.0001024971,0.0003792141,0.00008702368,0.0000276948,0.0001315579,0.000001014273,0.0002397923,0.9765517,0.01081998,0.0001757238,0.000008313553,0.01147547],"study_design_scores_gemma":[0.000726972,0.0007399013,0.0001950634,0.0001861443,0.000120405,0.0000053685,0.0001101981,0.9880389,0.009639179,0.0000448621,0.000009568543,0.0001834375],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1076401,0.00004657563,0.8913411,0.00000196747,0.0004612914,0.0003555811,0.00006471007,0.00003972732,0.00004892157],"genre_scores_gemma":[0.9983532,0.000002174105,0.001510495,0.000004852388,0.00005712308,0.00001842749,0.00002647546,0.00001968943,0.000007535215],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8907131,"threshold_uncertainty_score":0.8155396,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04357824447982828,"score_gpt":0.2425826519848666,"score_spread":0.1990044075050383,"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."}}