{"id":"W1976549066","doi":"10.1016/s0898-1221(04)90083-1","title":"Representation of differential operators in wavelet basis","year":2004,"lang":"en","type":"article","venue":"Computers & Mathematics with Applications","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University; University of Ottawa","funders":"","keywords":"Orthonormal basis; Mathematics; Representation (politics); Pure mathematics; Matrix representation; Separable space; Differential operator; Wavelet; Operator (biology); Matrix (chemical analysis); Basis (linear algebra); Operator theory; Algebra over a field; Mathematical analysis; Group (periodic table)","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":[],"consensus_categories":[],"category_scores_codex":[0.0001796136,0.0001136886,0.0002277673,0.0001647329,0.00006042473,0.00007585505,0.0005669252,0.00003564447,0.000003056913],"category_scores_gemma":[0.00001660428,0.00009632447,0.00004457439,0.0008691732,0.00005740181,0.0001949592,0.0001119322,0.00008422442,0.00001024883],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003964506,"about_ca_system_score_gemma":0.00006294216,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002043775,"about_ca_topic_score_gemma":0.000004673286,"domain_scores_codex":[0.9990049,0.00004762125,0.0003225637,0.0002598735,0.0002134994,0.0001515538],"domain_scores_gemma":[0.9989316,0.0001773875,0.0001268832,0.0006194357,0.00009264644,0.00005208348],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002124487,0.001208698,0.0003511879,0.0002129514,0.00006790032,0.00001579349,0.005790426,0.01001548,0.01048377,0.8881617,0.0001136737,0.08355721],"study_design_scores_gemma":[0.009079368,0.0004420996,0.01170573,0.0007616947,0.0001070623,0.0001779809,0.0004456088,0.2854052,0.2076527,0.4824359,0.0004706112,0.001315992],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0295693,0.00001467213,0.9690572,0.0002305314,0.00003552268,0.0003928694,0.000001418577,0.00005864312,0.0006398219],"genre_scores_gemma":[0.3416827,0.00000474926,0.6581511,0.00004272872,0.00001728831,0.00007763042,0.000003420626,0.000007431808,0.0000129086],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4057257,"threshold_uncertainty_score":0.3927998,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02083076544509345,"score_gpt":0.2857223863971028,"score_spread":0.2648916209520094,"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."}}