{"id":"W1993681020","doi":"10.1002/num.10092","title":"An immersed finite element space and its approximation capability","year":2004,"lang":"en","type":"article","venue":"Numerical Methods for Partial Differential Equations","topic":"Numerical methods in engineering","field":"Engineering","cited_by":200,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Finite element method; Sobolev space; Mathematics; Partition of unity; Interpolation (computer graphics); Mathematical analysis; Space (punctuation); Extended finite element method; Boundary value problem; Mixed finite element method; Function space; Partial differential equation; Boundary knot method; Applied mathematics; Boundary element method; Computer science; Physics; Classical mechanics","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":[0.0005493995,0.0003225313,0.0004301894,0.0001195208,0.0001774804,0.00007779491,0.0001824964,0.00015303,0.00007696309],"category_scores_gemma":[0.001307032,0.0003276539,0.0001370616,0.0003490459,0.00005472182,0.0002887802,0.00003799502,0.0002565975,0.000009642567],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001621898,"about_ca_system_score_gemma":0.00002367706,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001656912,"about_ca_topic_score_gemma":0.000001274949,"domain_scores_codex":[0.9980346,0.0002785002,0.0005351095,0.0004359666,0.0002016756,0.0005141379],"domain_scores_gemma":[0.9982092,0.0009707683,0.00007159213,0.0003369027,0.00008485246,0.0003266352],"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":[0.00004934364,0.0002574589,0.00001084752,0.0001804091,0.0001089585,4.634022e-7,0.0006570495,0.4853138,0.3139882,0.06885087,0.000003746241,0.1305788],"study_design_scores_gemma":[0.0007279201,0.0001944197,0.0002531623,0.00001413226,0.00008830391,9.416867e-7,0.00004782099,0.8924683,0.09321263,0.01226306,0.0003752875,0.0003540333],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009364747,0.0001309704,0.9881272,0.0001329704,0.000836375,0.0008208054,0.00004212209,0.0004813521,0.00006340898],"genre_scores_gemma":[0.5237344,0.000008403574,0.475801,0.00001378733,0.000140879,0.0002189838,0.00003476576,0.00004422902,0.000003582039],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5143697,"threshold_uncertainty_score":0.9999176,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04262816956017258,"score_gpt":0.3613179433050785,"score_spread":0.3186897737449059,"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."}}