{"id":"W2594035361","doi":"10.1109/antem.2004.7860675","title":"A preliminary approach to simulate parallel mesh refinement with Petri nets for 3-D finite element electromagnetics","year":2004,"lang":"en","type":"article","venue":"","topic":"Petri Nets in System Modeling","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Petri net; Computer science; Finite element method; Parallel computing; Computational science; Mesh generation; Electromagnetics; Software; Discrete event simulation; Computational electromagnetics; Parallel algorithm; Event (particle physics); Algorithm; Computer engineering; Distributed computing; Theoretical computer science; Simulation; Programming language; Engineering; Electronic engineering; Electromagnetic field; Structural engineering","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":[0.0005126377,0.0004666659,0.0003098557,0.0003106694,0.0004904528,0.0005392858,0.001091424,0.0006276667,0.002279502],"category_scores_gemma":[0.001165448,0.0003480845,0.0005467528,0.0002636809,0.0005115055,0.0004996408,0.0004346222,0.0009418668,0.0003699368],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006800228,"about_ca_system_score_gemma":0.001197757,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004967581,"about_ca_topic_score_gemma":0.006701054,"domain_scores_codex":[0.999783,0.00004085556,0.00001184432,0.00002425516,0.0001225007,0.00001756745],"domain_scores_gemma":[0.9996636,0.0001151879,0.00002185125,0.00006597065,0.0001142663,0.00001914551],"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":[0.00003664563,0.0000567162,0.0005746399,0.00006907256,0.00002020262,0.00006690313,0.0000708557,0.9282206,0.01600463,0.03262925,0.0004875074,0.02176284],"study_design_scores_gemma":[0.000008744652,0.00003893997,0.00006984492,0.000006096403,0.000005934979,0.00002555054,0.000008695405,0.9829653,0.007142005,0.005304045,0.004416582,0.000008264187],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005213778,0.00002102195,0.9924523,0.00004272193,0.00003018022,0.0000783729,0.00003462355,0.0003464793,0.001780414],"genre_scores_gemma":[0.1380556,0.0001357691,0.8587724,0.00004493622,0.00001271378,0.0003742218,0.0000952766,0.0001064209,0.00240265],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004967581,"threshold_uncertainty_score":0.009877324,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0251607742118014,"score_gpt":0.2514967025886056,"score_spread":0.2263359283768042,"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."}}