{"id":"W2775876351","doi":"","title":"Error estimation and adaption in domain decomposition methods","year":2017,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Model Reduction and Neural Networks","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Safran Electronics (Canada)","funders":"","keywords":"Computer science; Estimation; Decomposition; Algorithm; Engineering; Systems 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"],"consensus_categories":[],"category_scores_codex":[0.003126421,0.0002302843,0.0002789655,0.0001388937,0.0003124322,0.0003454449,0.0003644377,0.0001783191,0.0001251187],"category_scores_gemma":[0.00008034141,0.0002526131,0.0000981346,0.00008299249,0.0001238401,0.0001856065,0.0004585083,0.0005875247,0.000008697119],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005347549,"about_ca_system_score_gemma":0.00007678507,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001073247,"about_ca_topic_score_gemma":0.0002151771,"domain_scores_codex":[0.9954852,0.003276294,0.0003585333,0.0005208693,0.0001551935,0.0002039528],"domain_scores_gemma":[0.9978049,0.0003846147,0.0004513501,0.0009324168,0.0003211215,0.0001055426],"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":[0.00002613404,0.0003907139,0.002339843,0.00009031733,0.0000585735,0.000001363544,0.004306264,0.003337614,0.002257545,0.1365364,0.0005026635,0.8501526],"study_design_scores_gemma":[0.0009800909,5.542529e-7,0.007848434,0.001866769,0.00005520329,0.000006086181,0.0001803383,0.803126,0.01641987,0.1642377,0.004634338,0.0006446535],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1914413,0.0002888561,0.7845606,0.002939358,0.0001702139,0.0003452719,0.00002319463,0.00005748716,0.02017374],"genre_scores_gemma":[0.8044196,0.00009356126,0.1932645,0.0000168921,0.00004003438,0.00007416293,0.0005384925,0.00002215669,0.001530599],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8495079,"threshold_uncertainty_score":0.9999926,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02581946384969171,"score_gpt":0.3214484368918397,"score_spread":0.295628973042148,"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."}}