{"id":"W4416428089","doi":"10.1016/j.apnum.2025.11.009","title":"A derivative-orthogonal wavelet multiscale method for elliptic equations with rough diffusion coefficients","year":2025,"lang":"en","type":"article","venue":"Applied Numerical Mathematics","topic":"Advanced Mathematical Modeling in Engineering","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; King Fahd University of Petroleum and Minerals; University of Pittsburgh","keywords":"Wavelet; Bounded function; Basis function; Interpolation (computer graphics); Matrix (chemical analysis); Basis (linear algebra); Numerical analysis; Condition number; Function (biology); Sobolev space","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.0002568521,0.0002827426,0.0004394723,0.0001158538,0.0001994781,0.00008561344,0.0006372405,0.00008762813,0.000004991523],"category_scores_gemma":[0.0003370889,0.0002247383,0.00008148052,0.0007488698,0.00005378076,0.00012504,0.0002592669,0.0001866546,0.00001978355],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007649943,"about_ca_system_score_gemma":0.00004900815,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":7.366364e-7,"about_ca_topic_score_gemma":2.484034e-7,"domain_scores_codex":[0.9982231,0.00001794581,0.0004878026,0.0004845562,0.0003533836,0.0004331577],"domain_scores_gemma":[0.9968409,0.002166116,0.0001409308,0.0006241301,0.0001199532,0.0001079691],"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":[0.00001024754,0.0003862794,0.000001478795,0.0002270731,0.0000368835,9.745372e-7,0.0005343826,0.06893216,0.001720386,0.9145159,0.00002972067,0.01360455],"study_design_scores_gemma":[0.0005586052,0.00004679471,0.000008018437,0.00009706905,0.00003006412,0.00000341206,0.00004474832,0.8471599,0.001369176,0.1501627,0.0002934281,0.0002260817],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0006430994,0.0000142195,0.9964591,0.0002939196,0.0000775658,0.0008897557,0.000004995416,0.0003364874,0.001280868],"genre_scores_gemma":[0.1655028,0.000001245369,0.8337411,0.000193204,0.00001804612,0.0003816862,0.000005376223,0.00002843449,0.0001280385],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7782277,"threshold_uncertainty_score":0.9164563,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01576886328955445,"score_gpt":0.2861892677240074,"score_spread":0.270420404434453,"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."}}