{"id":"W2172258891","doi":"10.4028/www.scientific.net/amm.117-119.489","title":"Scalability Study on Large-Scale Parallel Finite Element Computing in PANDA Frame","year":2011,"lang":"en","type":"article","venue":"Applied Mechanics and Materials","topic":"Electromagnetic Simulation and Numerical Methods","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Association of Emergency Physicians","funders":"","keywords":"Speedup; Parallel computing; Scalability; Computer science; Computation; Frame (networking); Scale (ratio); Finite element method; Supercomputer; Computational science; Parallel algorithm; Process (computing); Grid; Algorithm; Mathematics; Physics; Engineering; Geometry; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006682434,0.0001358578,0.000253251,0.00004464771,0.00003611825,0.00002148657,0.00006430604,0.00006371492,0.0001736215],"category_scores_gemma":[0.00001467366,0.0001255148,0.00001328224,0.00008615083,0.000004047463,0.00001469968,0.00004414712,0.000079046,0.00001101095],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001828156,"about_ca_system_score_gemma":0.000003149528,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001149663,"about_ca_topic_score_gemma":0.000006165538,"domain_scores_codex":[0.999105,0.00005741477,0.0002978882,0.0002045416,0.00009205307,0.0002430422],"domain_scores_gemma":[0.9996578,0.00008256291,0.00003152643,0.0001623215,0.000009302353,0.0000564677],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.001213615,0.00452311,0.00284766,0.000557798,0.0002574541,0.00002804081,0.02969568,0.007049107,0.4629465,0.4333756,0.000125064,0.05738035],"study_design_scores_gemma":[0.01661314,0.004675074,0.1269542,0.0001571245,0.0001734123,0.000004328428,0.005857175,0.1992466,0.277639,0.3639402,0.001876906,0.002862879],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8013559,0.00001130425,0.1973007,0.000004751549,0.000165292,0.0004496051,0.000006175851,0.00008906139,0.0006172857],"genre_scores_gemma":[0.9706036,0.00001290985,0.02921169,0.00008153285,0.00002427693,0.00003979002,0.000003807435,0.00001881727,0.000003553466],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1921975,"threshold_uncertainty_score":0.5118345,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02326094838282344,"score_gpt":0.2586658179439037,"score_spread":0.2354048695610803,"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."}}