{"id":"W2344286654","doi":"10.22215/etd/2009-06666","title":"Waveform relaxation and transverse partitioning algorithms for simulation of massively coupled interconnects","year":2009,"lang":"en","type":"dissertation","venue":"","topic":"Electromagnetic Compatibility and Noise Suppression","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Library and Archives Canada","funders":"","keywords":"Waveform; Physics; Algorithm; Computer science; Transverse plane; Massively parallel; Relaxation (psychology); Parallel computing; Telecommunications; Engineering; Psychology","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":[0.00009543468,0.0001719199,0.0002506126,0.0001159777,0.00005108283,0.00001627207,0.00004531577,0.0002109555,0.00005405154],"category_scores_gemma":[0.00005464036,0.0001715233,0.00007143492,0.0000779665,0.000009907892,0.0001380331,0.000001910033,0.0001208428,0.000001109405],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004211346,"about_ca_system_score_gemma":0.0000174585,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001749025,"about_ca_topic_score_gemma":0.0003386892,"domain_scores_codex":[0.9992079,0.00001084487,0.0003501062,0.0001762617,0.0001155067,0.0001394155],"domain_scores_gemma":[0.9994912,0.0001496434,0.00009132936,0.0001051005,0.0001243261,0.00003843845],"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":[0.0009981664,0.0001905486,0.00004957815,0.00514451,0.0002271197,0.00000231323,0.008288249,0.4470409,0.207892,0.00134778,0.0005083558,0.3283105],"study_design_scores_gemma":[0.0005981014,0.0003019025,0.002590311,0.0003702376,0.00006862334,4.878243e-7,0.0002826677,0.9568526,0.03686801,0.00176084,0.000111723,0.0001944882],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9780756,0.0002264058,0.0185478,0.000017932,0.0001887523,0.0006472665,0.00001726934,0.0001366173,0.002142331],"genre_scores_gemma":[0.9960246,0.00006635633,0.001979112,0.00000405267,0.00003785858,0.00003298447,0.001268743,0.00002100829,0.0005652835],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5098118,"threshold_uncertainty_score":0.6994515,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01312223031089221,"score_gpt":0.2563289330759766,"score_spread":0.2432067027650844,"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."}}