{"id":"W2604483461","doi":"","title":"An adaptive choice of primal constrains for BDDC domain decomposition algorithms","year":2016,"lang":"en","type":"article","venue":"ETNA - Electronic Transactions on Numerical Analysis","topic":"Advanced Numerical Methods in Computational Mathematics","field":"Engineering","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mathematics; Schur complement; Preconditioner; Domain decomposition methods; Eigenvalues and eigenvectors; Upper and lower bounds; Norm (philosophy); Condition number; Schur decomposition; Conjugate gradient method; Algorithm; Finite element method; Iterative method; Mathematical analysis","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001566243,0.001031369,0.0007469488,0.0007084149,0.0006554589,0.001219785,0.001304822,0.0007997833,0.002576262],"category_scores_gemma":[0.004608667,0.0006299426,0.0003961401,0.0006916476,0.00111577,0.001179771,0.002118804,0.002115346,0.0006668237],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006668434,"about_ca_system_score_gemma":0.0006674341,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006357497,"about_ca_topic_score_gemma":0.0009554674,"domain_scores_codex":[0.9989711,0.0003814634,0.0000513447,0.0001097707,0.0004274335,0.00005888967],"domain_scores_gemma":[0.9986719,0.0006269971,0.0001170232,0.0001616629,0.0003421907,0.00008032163],"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":[0.0005380965,0.0002507352,0.002041296,0.0003994319,0.00006009588,0.0002188368,0.0002101647,0.4881938,0.04459563,0.2337944,0.00384934,0.2258483],"study_design_scores_gemma":[0.00001667893,0.00003564115,0.00007664674,0.00002271495,0.000005279197,0.00003637369,0.000009732152,0.9821386,0.003750901,0.01145833,0.002438038,0.0000110188],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009503825,0.0001823578,0.9877073,0.0001026444,0.00003204971,0.00004006653,0.00002878133,0.00008325962,0.002319784],"genre_scores_gemma":[0.2358515,0.0003352031,0.7603958,0.0001197201,0.00009380002,0.0003187986,0.0001307474,0.0002523632,0.002502054],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002576262,"threshold_uncertainty_score":0.008618474,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01748277575701655,"score_gpt":0.3256021547602164,"score_spread":0.3081193790031999,"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."}}