{"id":"W3196108459","doi":"10.11159/eee21.110","title":"Modified Parareal Algorithm for Solving Time-Dependent Differential Equations","year":2021,"lang":"en","type":"article","venue":"Proceedings of the World Congress on Electrical Engineering and Computer Systems and Science","topic":"Numerical methods for differential equations","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Division of Electrical, Communications and Cyber Systems; National Science Foundation","keywords":"Computer science; Differential equation; Algorithm; Applied mathematics; Mathematical optimization; Mathematics; Mathematical analysis","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003088817,0.0001347234,0.0002732746,0.0001361465,0.0002347635,0.0002226925,0.0002371474,0.00003303817,9.511081e-7],"category_scores_gemma":[0.0003323646,0.00009781787,0.00005716046,0.0005238497,0.00008345281,0.0001016552,0.0001381219,0.0001206952,1.533013e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003261131,"about_ca_system_score_gemma":0.00003270336,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004198175,"about_ca_topic_score_gemma":4.25715e-7,"domain_scores_codex":[0.998823,0.000008295751,0.0002671115,0.0003051496,0.0003341603,0.0002622071],"domain_scores_gemma":[0.9988368,0.0005904675,0.0001195817,0.00009667195,0.0002532892,0.0001032407],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000219812,0.0002978735,0.00008906185,0.0004614037,0.0001294797,0.000001166243,0.0002151209,0.002066297,0.05738145,0.8134231,0.0003203766,0.1255927],"study_design_scores_gemma":[0.0002476284,0.00006241644,0.0001175192,0.0001466263,0.00003176621,0.000009252578,0.000004365411,0.988739,0.005959488,0.004516166,0.00004310783,0.0001226628],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06426512,0.0001171091,0.9339039,0.0001193991,0.001042103,0.0003892528,0.00000852676,0.00007347616,0.00008107485],"genre_scores_gemma":[0.9412739,0.000006356502,0.05702678,0.00001606786,0.0002226056,0.00007044509,5.596766e-7,0.00001925498,0.001364049],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9866727,"threshold_uncertainty_score":0.3988897,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02489726315801668,"score_gpt":0.2726135500581058,"score_spread":0.2477162869000891,"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."}}