{"id":"W2955880941","doi":"","title":"Nonlinearly preconditioned FETI method","year":2019,"lang":"fr","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Numerical methods in engineering","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Safran Electronics (Canada)","funders":"","keywords":"Domain decomposition methods; Nonlinear system; Finite element method; FETI; Computer science; Applied mathematics; Partial differential equation; Mathematics; Mathematical analysis; Physics; Structural engineering; 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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.009470856,0.0008820057,0.001052525,0.0003429855,0.0002684203,0.000486911,0.001933665,0.0008706965,0.001303169],"category_scores_gemma":[0.003492345,0.001094589,0.000544289,0.0007836796,0.0002127258,0.000335747,0.001345967,0.00214685,0.0009119515],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005858083,"about_ca_system_score_gemma":0.000241531,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001055322,"about_ca_topic_score_gemma":0.0001772636,"domain_scores_codex":[0.9871883,0.008732696,0.001187455,0.001323895,0.0006431248,0.0009244878],"domain_scores_gemma":[0.9870918,0.006718616,0.0004963496,0.003518779,0.001721144,0.0004533537],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002223843,0.0008904804,0.001140727,0.002278429,0.0008632684,0.00002272975,0.01102315,0.2178797,0.03278983,0.2519226,0.002049634,0.4791172],"study_design_scores_gemma":[0.0009036203,9.592575e-7,0.005196563,0.004217412,0.0002068267,0.00004984585,0.0001044182,0.7523628,0.1125422,0.01050974,0.1123103,0.001595265],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006239978,0.002335813,0.9020241,0.005763647,0.002366779,0.0008167503,0.0002236129,0.0008391844,0.07939014],"genre_scores_gemma":[0.03731113,0.0008419189,0.9298633,0.00006901446,0.0001533904,0.0001629878,0.0004919406,0.0002749701,0.03083138],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5344831,"threshold_uncertainty_score":0.9998659,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01493722583649909,"score_gpt":0.2587095313456406,"score_spread":0.2437723055091415,"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."}}